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DICE: Leveraging Sparsification for Out-of-Distribution Detection
| 25 |
eccv
| 6 | 0 |
2023-06-17 00:59:09.612000
|
https://github.com/deeplearning-wisc/dice
| 30 |
Dice: Leveraging sparsification for out-of-distribution detection
|
https://scholar.google.com/scholar?cluster=878626789575390648&hl=en&as_sdt=0,33
| 3 | 2,022 |
Invariant Feature Learning for Generalized Long-Tailed Classification
| 12 |
eccv
| 8 | 2 |
2023-06-17 00:59:09.823000
|
https://github.com/kaihuatang/generalized-long-tailed-benchmarks.pytorch
| 99 |
Invariant feature learning for generalized long-tailed classification
|
https://scholar.google.com/scholar?cluster=2921674289381974673&hl=en&as_sdt=0,5
| 2 | 2,022 |
Sliced Recursive Transformer
| 12 |
eccv
| 10 | 0 |
2023-06-17 00:59:10.035000
|
https://github.com/szq0214/sret
| 55 |
Sliced recursive transformer
|
https://scholar.google.com/scholar?cluster=6881440757906382227&hl=en&as_sdt=0,11
| 6 | 2,022 |
Cross-Domain Ensemble Distillation for Domain Generalization
| 3 |
eccv
| 5 | 1 |
2023-06-17 00:59:10.249000
|
https://github.com/leekyungmoon/XDED
| 20 |
Cross-domain Ensemble Distillation for Domain Generalization
|
https://scholar.google.com/scholar?cluster=7614016061271891852&hl=en&as_sdt=0,5
| 4 | 2,022 |
Centrality and Consistency: Two-Stage Clean Samples Identification for Learning with Instance-Dependent Noisy Labels
| 2 |
eccv
| 2 | 3 |
2023-06-17 00:59:10.462000
|
https://github.com/uitrbn/tscsi_idn
| 8 |
Centrality and consistency: two-stage clean samples identification for learning with instance-dependent noisy labels
|
https://scholar.google.com/scholar?cluster=17182529425583795058&hl=en&as_sdt=0,5
| 1 | 2,022 |
VL-LTR: Learning Class-Wise Visual-Linguistic Representation for Long-Tailed Visual Recognition
| 15 |
eccv
| 10 | 6 |
2023-06-17 00:59:10.674000
|
https://github.com/ChangyaoTian/VL-LTR
| 51 |
Vl-ltr: Learning class-wise visual-linguistic representation for long-tailed visual recognition
|
https://scholar.google.com/scholar?cluster=3647078390700500997&hl=en&as_sdt=0,32
| 3 | 2,022 |
Class Is Invariant to Context and Vice Versa: On Learning Invariance for Out-of-Distribution Generalization
| 3 |
eccv
| 0 | 0 |
2023-06-17 00:59:10.890000
|
https://github.com/simpleshinobu/irmcon
| 16 |
Class is invariant to context and vice versa: on learning invariance for out-of-distribution generalization
|
https://scholar.google.com/scholar?cluster=10029134243700219683&hl=en&as_sdt=0,5
| 0 | 2,022 |
Hierarchical Semi-Supervised Contrastive Learning for Contamination-Resistant Anomaly Detection
| 2 |
eccv
| 1 | 0 |
2023-06-17 00:59:11.105000
|
https://github.com/gaoangw/hscl
| 7 |
Hierarchical Semi-supervised Contrastive Learning for Contamination-Resistant Anomaly Detection
|
https://scholar.google.com/scholar?cluster=13983761419031899211&hl=en&as_sdt=0,31
| 1 | 2,022 |
RealPatch: A Statistical Matching Framework for Model Patching with Real Samples
| 1 |
eccv
| 0 | 0 |
2023-06-17 00:59:11.321000
|
https://github.com/wearepal/realpatch
| 2 |
RealPatch: A Statistical Matching Framework for Model Patching with Real Samples
|
https://scholar.google.com/scholar?cluster=16389603249076638788&hl=en&as_sdt=0,33
| 2 | 2,022 |
Semantic Novelty Detection via Relational Reasoning
| 0 |
eccv
| 0 | 0 |
2023-06-17 00:59:11.534000
|
https://github.com/francescocappio/resend
| 14 |
Semantic Novelty Detection via Relational Reasoning
|
https://scholar.google.com/scholar?cluster=2885314653619622739&hl=en&as_sdt=0,5
| 1 | 2,022 |
Training Vision Transformers with Only 2040 Images
| 14 |
eccv
| 4 | 2 |
2023-06-17 00:59:11.745000
|
https://github.com/CupidJay/Training-Vision-Transformers-with-only-2040-images
| 43 |
Training vision transformers with only 2040 images
|
https://scholar.google.com/scholar?cluster=15808243844725790365&hl=en&as_sdt=0,31
| 2 | 2,022 |
TDAM: Top-Down Attention Module for Contextually Guided Feature Selection in CNNs
| 3 |
eccv
| 0 | 0 |
2023-06-17 00:59:11.957000
|
https://github.com/shantanuj/tdam_top_down_attention_module
| 6 |
TDAM: Top-Down Attention Module for Contextually Guided Feature Selection in CNNs
|
https://scholar.google.com/scholar?cluster=10902957044896292324&hl=en&as_sdt=0,44
| 1 | 2,022 |
Automatic Check-Out via Prototype-Based Classifier Learning from Single-Product Exemplars
| 1 |
eccv
| 0 | 2 |
2023-06-17 00:59:12.190000
|
https://github.com/hao-chen-njust/psp
| 1 |
Automatic Check-Out via Prototype-Based Classifier Learning from Single-Product Exemplars
|
https://scholar.google.com/scholar?cluster=9346886979579970159&hl=en&as_sdt=0,5
| 1 | 2,022 |
Overcoming Shortcut Learning in a Target Domain by Generalizing Basic Visual Factors from a Source Domain
| 1 |
eccv
| 0 | 0 |
2023-06-17 00:59:12.402000
|
https://github.com/boschresearch/sourcegen
| 1 |
Overcoming Shortcut Learning in a Target Domain by Generalizing Basic Visual Factors from a Source Domain
|
https://scholar.google.com/scholar?cluster=11823647734753043783&hl=en&as_sdt=0,5
| 3 | 2,022 |
Wave-ViT: Unifying Wavelet and Transformers for Visual Representation Learning
| 28 |
eccv
| 21 | 6 |
2023-06-17 00:59:12.620000
|
https://github.com/yehli/imagenetmodel
| 109 |
Wave-vit: Unifying wavelet and transformers for visual representation learning
|
https://scholar.google.com/scholar?cluster=9894263145711509588&hl=en&as_sdt=0,5
| 5 | 2,022 |
Tailoring Self-Supervision for Supervised Learning
| 5 |
eccv
| 3 | 0 |
2023-06-17 00:59:12.833000
|
https://github.com/wjun0830/localizable-rotation
| 19 |
Tailoring Self-Supervision for Supervised Learning
|
https://scholar.google.com/scholar?cluster=7286213705306968536&hl=en&as_sdt=0,33
| 4 | 2,022 |
Difficulty-Aware Simulator for Open Set Recognition
| 5 |
eccv
| 2 | 0 |
2023-06-17 00:59:13.046000
|
https://github.com/wjun0830/difficulty-aware-simulator
| 24 |
Difficulty-Aware Simulator for Open Set Recognition
|
https://scholar.google.com/scholar?cluster=13965399748614059565&hl=en&as_sdt=0,5
| 1 | 2,022 |
Few-Shot Class-Incremental Learning from an Open-Set Perspective
| 14 |
eccv
| 3 | 0 |
2023-06-17 00:59:13.259000
|
https://github.com/canpeng123/fscil_alice
| 19 |
Few-Shot Class-Incremental Learning from an Open-Set Perspective
|
https://scholar.google.com/scholar?cluster=16116173187693664231&hl=en&as_sdt=0,47
| 2 | 2,022 |
FOSTER: Feature Boosting and Compression for Class-Incremental Learning
| 34 |
eccv
| 0 | 2 |
2023-06-17 00:59:13.471000
|
https://github.com/G-U-N/ECCV22-FOSTER
| 31 |
Foster: Feature boosting and compression for class-incremental learning
|
https://scholar.google.com/scholar?cluster=17421080525009780737&hl=en&as_sdt=0,33
| 3 | 2,022 |
Visual Knowledge Tracing
| 0 |
eccv
| 1 | 0 |
2023-06-17 00:59:13.685000
|
https://github.com/nkondapa/visualknowledgetracing
| 13 |
Visual Knowledge Tracing
|
https://scholar.google.com/scholar?cluster=17421247468685964476&hl=en&as_sdt=0,8
| 1 | 2,022 |
Improving Fine-Grained Visual Recognition in Low Data Regimes via Self-Boosting Attention Mechanism
| 3 |
eccv
| 4 | 7 |
2023-06-17 00:59:13.899000
|
https://github.com/ganperf/sam
| 19 |
Improving fine-grained visual recognition in low data regimes via self-boosting attention mechanism
|
https://scholar.google.com/scholar?cluster=1093309124842032174&hl=en&as_sdt=0,5
| 3 | 2,022 |
VSA: Learning Varied-Size Window Attention in Vision Transformers
| 25 |
eccv
| 6 | 5 |
2023-06-17 00:59:14.113000
|
https://github.com/vitae-transformer/vitae-vsa
| 132 |
VSA: learning varied-size window attention in vision transformers
|
https://scholar.google.com/scholar?cluster=7134900495559356797&hl=en&as_sdt=0,5
| 2 | 2,022 |
DenseHybrid: Hybrid Anomaly Detection for Dense Open-Set Recognition
| 14 |
eccv
| 3 | 2 |
2023-06-17 00:59:14.326000
|
https://github.com/matejgrcic/DenseHybrid
| 20 |
Densehybrid: Hybrid anomaly detection for dense open-set recognition
|
https://scholar.google.com/scholar?cluster=17117872304717676783&hl=en&as_sdt=0,36
| 2 | 2,022 |
Rethinking Confidence Calibration for Failure Prediction
| 7 |
eccv
| 1 | 0 |
2023-06-17 00:59:14.542000
|
https://github.com/impression2805/fmfp
| 13 |
Rethinking Confidence Calibration for Failure Prediction
|
https://scholar.google.com/scholar?cluster=3192244699956049091&hl=en&as_sdt=0,5
| 2 | 2,022 |
Uncertainty-Guided Source-Free Domain Adaptation
| 14 |
eccv
| 3 | 2 |
2023-06-17 00:59:14.759000
|
https://github.com/roysubhankar/uncertainty-sfda
| 31 |
Uncertainty-guided source-free domain adaptation
|
https://scholar.google.com/scholar?cluster=10598112265751424023&hl=en&as_sdt=0,44
| 4 | 2,022 |
Should All Proposals Be Treated Equally in Object Detection?
| 0 |
eccv
| 1 | 0 |
2023-06-17 00:59:14.974000
|
https://github.com/liyunsheng13/dpp
| 31 |
Should All Proposals Be Treated Equally in Object Detection?
|
https://scholar.google.com/scholar?cluster=12493352248493160142&hl=en&as_sdt=0,24
| 6 | 2,022 |
PRIME: A Few Primitives Can Boost Robustness to Common Corruptions
| 12 |
eccv
| 5 | 1 |
2023-06-17 00:59:15.192000
|
https://github.com/amodas/PRIME-augmentations
| 38 |
PRIME: A few primitives can boost robustness to common corruptions
|
https://scholar.google.com/scholar?cluster=4562095737228687677&hl=en&as_sdt=0,11
| 3 | 2,022 |
In Defense of Image Pre-training for Spatiotemporal Recognition
| 0 |
eccv
| 0 | 1 |
2023-06-17 00:59:15.422000
|
https://github.com/ucsc-vlaa/image-pretraining-for-video
| 17 |
In Defense of Image Pre-Training for Spatiotemporal Recognition
|
https://scholar.google.com/scholar?cluster=18269323448808190712&hl=en&as_sdt=0,33
| 0 | 2,022 |
Augmenting Deep Classifiers with Polynomial Neural Networks
| 5 |
eccv
| 0 | 0 |
2023-06-17 00:59:15.636000
|
https://github.com/grigorisg9gr/polynomials-for-augmenting-nns
| 2 |
Augmenting deep classifiers with polynomial neural networks
|
https://scholar.google.com/scholar?cluster=14218781642284557592&hl=en&as_sdt=0,5
| 2 | 2,022 |
Learning with Noisy Labels by Efficient Transition Matrix Estimation to Combat Label Miscorrection
| 3 |
eccv
| 1 | 1 |
2023-06-17 00:59:15.849000
|
https://github.com/hyperconnect/fasten
| 6 |
Learning with Noisy Labels by Efficient Transition Matrix Estimation to Combat Label Miscorrection
|
https://scholar.google.com/scholar?cluster=13055133803881493745&hl=en&as_sdt=0,5
| 7 | 2,022 |
Contrastive Deep Supervision
| 7 |
eccv
| 3 | 1 |
2023-06-17 00:59:16.064000
|
https://github.com/archiplab-linfengzhang/contrastive-deep-supervision
| 50 |
Contrastive deep supervision
|
https://scholar.google.com/scholar?cluster=7265954552843581197&hl=en&as_sdt=0,44
| 3 | 2,022 |
Discriminability-Transferability Trade-Off: An Information-Theoretic Perspective
| 7 |
eccv
| 0 | 0 |
2023-06-17 00:59:16.281000
|
https://github.com/dtennant/dt-tradeoff
| 5 |
Discriminability-transferability trade-off: an information-theoretic perspective
|
https://scholar.google.com/scholar?cluster=4648654949432885317&hl=en&as_sdt=0,33
| 1 | 2,022 |
LocVTP: Video-Text Pre-training for Temporal Localization
| 22 |
eccv
| 0 | 4 |
2023-06-17 00:59:16.494000
|
https://github.com/mengcaopku/locvtp
| 34 |
Locvtp: Video-text pre-training for temporal localization
|
https://scholar.google.com/scholar?cluster=12927720534552603420&hl=en&as_sdt=0,5
| 2 | 2,022 |
Learning Ego 3D Representation As Ray Tracing
| 14 |
eccv
| 5 | 2 |
2023-06-17 00:59:16.712000
|
https://github.com/fudan-zvg/ego3rt
| 92 |
Learning ego 3d representation as ray tracing
|
https://scholar.google.com/scholar?cluster=11031442758029473428&hl=en&as_sdt=0,33
| 12 | 2,022 |
Static and Dynamic Concepts for Self-Supervised Video Representation Learning
| 3 |
eccv
| 1 | 1 |
2023-06-17 00:59:16.925000
|
https://github.com/shvdiwnkozbw/Self-supervised-Video-Concept
| 10 |
Static and Dynamic Concepts for Self-supervised Video Representation Learning
|
https://scholar.google.com/scholar?cluster=2899262297077900123&hl=en&as_sdt=0,5
| 1 | 2,022 |
Hierarchically Self-Supervised Transformer for Human Skeleton Representation Learning
| 8 |
eccv
| 2 | 1 |
2023-06-17 00:59:17.138000
|
https://github.com/yuxiaochen1103/Hi-TRS
| 18 |
Hierarchically Self-supervised Transformer for Human Skeleton Representation Learning
|
https://scholar.google.com/scholar?cluster=17795536636846688217&hl=en&as_sdt=0,5
| 1 | 2,022 |
CoSCL: Cooperation of Small Continual Learners Is Stronger than a Big One
| 3 |
eccv
| 2 | 0 |
2023-06-17 00:59:17.350000
|
https://github.com/lywang3081/coscl
| 12 |
CoSCL: Cooperation of Small Continual Learners is Stronger Than a Big One
|
https://scholar.google.com/scholar?cluster=10311122253648677302&hl=en&as_sdt=0,41
| 1 | 2,022 |
Fast-MoCo: Boost Momentum-Based Contrastive Learning with Combinatorial Patches
| 3 |
eccv
| 0 | 0 |
2023-06-17 00:59:17.562000
|
https://github.com/orashi/fast-moco
| 9 |
Fast-MoCo: Boost Momentum-Based Contrastive Learning with Combinatorial Patches
|
https://scholar.google.com/scholar?cluster=3809897863505864658&hl=en&as_sdt=0,5
| 1 | 2,022 |
LoRD: Local 4D Implicit Representation for High-Fidelity Dynamic Human Modeling
| 2 |
eccv
| 6 | 0 |
2023-06-17 00:59:17.774000
|
https://github.com/BoyanJIANG/LoRD
| 57 |
LoRD: Local 4D Implicit Representation for High-Fidelity Dynamic Human Modeling
|
https://scholar.google.com/scholar?cluster=18207490584500698956&hl=en&as_sdt=0,10
| 4 | 2,022 |
On the Versatile Uses of Partial Distance Correlation in Deep Learning
| 5 |
eccv
| 16 | 0 |
2023-06-17 00:59:17.986000
|
https://github.com/zhenxingjian/partial_distance_correlation
| 162 |
On the versatile uses of partial distance correlation in deep learning
|
https://scholar.google.com/scholar?cluster=17295760961898440654&hl=en&as_sdt=0,38
| 4 | 2,022 |
DAS: Densely-Anchored Sampling for Deep Metric Learning
| 4 |
eccv
| 1 | 0 |
2023-06-17 00:59:18.199000
|
https://github.com/lizhaoliu-Lec/DAS
| 14 |
Das: Densely-anchored sampling for deep metric learning
|
https://scholar.google.com/scholar?cluster=13410935767802137885&hl=en&as_sdt=0,5
| 2 | 2,022 |
Learn from All: Erasing Attention Consistency for Noisy Label Facial Expression Recognition
| 31 |
eccv
| 8 | 5 |
2023-06-17 00:59:18.410000
|
https://github.com/zyh-uaiaaaa/erasing-attention-consistency
| 48 |
Learn from all: Erasing attention consistency for noisy label facial expression recognition
|
https://scholar.google.com/scholar?cluster=3230431190406827600&hl=en&as_sdt=0,5
| 2 | 2,022 |
A Non-Isotropic Probabilistic Take On Proxy-Based Deep Metric Learning
| 3 |
eccv
| 0 | 0 |
2023-06-17 00:59:18.623000
|
https://github.com/explainableml/probabilistic_deep_metric_learning
| 11 |
A Non-isotropic Probabilistic Take on Proxy-based Deep Metric Learning
|
https://scholar.google.com/scholar?cluster=18270830460222491727&hl=en&as_sdt=0,5
| 8 | 2,022 |
TokenMix: Rethinking Image Mixing for Data Augmentation in Vision Transformers
| 17 |
eccv
| 8 | 6 |
2023-06-17 00:59:18.841000
|
https://github.com/sense-x/tokenmix
| 85 |
Tokenmix: Rethinking image mixing for data augmentation in vision transformers
|
https://scholar.google.com/scholar?cluster=8406088123118572709&hl=en&as_sdt=0,5
| 6 | 2,022 |
Sound Localization by Self-Supervised Time Delay Estimation
| 6 |
eccv
| 5 | 0 |
2023-06-17 00:59:19.053000
|
https://github.com/IFICL/stereocrw
| 10 |
Sound Localization by Self-Supervised Time Delay Estimation
|
https://scholar.google.com/scholar?cluster=13725278977691156575&hl=en&as_sdt=0,5
| 1 | 2,022 |
SLIP: Self-Supervision Meets Language-Image Pre-training
| 163 |
eccv
| 61 | 18 |
2023-06-17 00:59:19.266000
|
https://github.com/facebookresearch/slip
| 672 |
Slip: Self-supervision meets language-image pre-training
|
https://scholar.google.com/scholar?cluster=17384094251372134587&hl=en&as_sdt=0,5
| 16 | 2,022 |
A Contrastive Objective for Learning Disentangled Representations
| 7 |
eccv
| 0 | 0 |
2023-06-17 00:59:19.478000
|
https://github.com/jonkahana/dcodr
| 4 |
A contrastive objective for learning disentangled representations
|
https://scholar.google.com/scholar?cluster=17352506721201259151&hl=en&as_sdt=0,10
| 1 | 2,022 |
PT4AL: Using Self-Supervised Pretext Tasks for Active Learning
| 4 |
eccv
| 2 | 6 |
2023-06-17 00:59:19.690000
|
https://github.com/johnsk95/pt4al
| 45 |
PT4AL: Using Self-supervised Pretext Tasks for Active Learning
|
https://scholar.google.com/scholar?cluster=11229213520949185993&hl=en&as_sdt=0,5
| 5 | 2,022 |
DualPrompt: Complementary Prompting for Rehearsal-Free Continual Learning
| 62 |
eccv
| 33 | 4 |
2023-06-17 00:59:19.902000
|
https://github.com/google-research/l2p
| 284 |
Dualprompt: Complementary prompting for rehearsal-free continual learning
|
https://scholar.google.com/scholar?cluster=7069579101447184812&hl=en&as_sdt=0,10
| 7 | 2,022 |
Joint Learning of Localized Representations from Medical Images and Reports
| 20 |
eccv
| 3 | 0 |
2023-06-17 00:59:20.114000
|
https://github.com/philip-mueller/lovt
| 12 |
Joint learning of localized representations from medical images and reports
|
https://scholar.google.com/scholar?cluster=9049923034415496270&hl=en&as_sdt=0,31
| 1 | 2,022 |
Identifying Hard Noise in Long-Tailed Sample Distribution
| 4 |
eccv
| 1 | 4 |
2023-06-17 00:59:20.327000
|
https://github.com/yxymessi/h2e-framework
| 71 |
Identifying Hard Noise in Long-Tailed Sample Distribution
|
https://scholar.google.com/scholar?cluster=5820418443271560279&hl=en&as_sdt=0,5
| 5 | 2,022 |
NashAE: Disentangling Representations through Adversarial Covariance Minimization
| 1 |
eccv
| 1 | 0 |
2023-06-17 00:59:20.539000
|
https://github.com/ericyeats/nashae-beamsynthesis
| 3 |
NashAE: Disentangling Representations Through Adversarial Covariance Minimization
|
https://scholar.google.com/scholar?cluster=11326949042914417761&hl=en&as_sdt=0,33
| 1 | 2,022 |
Learning Visual Representation from Modality-Shared Contrastive Language-Image Pre-training
| 16 |
eccv
| 2 | 0 |
2023-06-17 00:59:20.752000
|
https://github.com/hxyou/msclip
| 64 |
Learning visual representation from modality-shared contrastive language-image pre-training
|
https://scholar.google.com/scholar?cluster=4379401598499228953&hl=en&as_sdt=0,5
| 4 | 2,022 |
Contrasting Quadratic Assignments for Set-Based Representation Learning
| 3 |
eccv
| 0 | 0 |
2023-06-17 00:59:20.964000
|
https://github.com/amoskalev/contrasting_quadratic
| 8 |
Contrasting quadratic assignments for set-based representation learning
|
https://scholar.google.com/scholar?cluster=6929984875841062884&hl=en&as_sdt=0,33
| 2 | 2,022 |
Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer
| 7 |
eccv
| 0 | 4 |
2023-06-17 00:59:21.190000
|
https://github.com/ashok-arjun/CSCCT
| 13 |
Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer
|
https://scholar.google.com/scholar?cluster=18267860036724176528&hl=en&as_sdt=0,39
| 1 | 2,022 |
MVDG: A Unified Multi-View Framework for Domain Generalization
| 4 |
eccv
| 0 | 1 |
2023-06-17 00:59:21.403000
|
https://github.com/koncle/mvdg
| 4 |
MVDG: A Unified Multi-view Framework for Domain Generalization
|
https://scholar.google.com/scholar?cluster=3734859660298356325&hl=en&as_sdt=0,5
| 1 | 2,022 |
Panoptic Scene Graph Generation
| 17 |
eccv
| 53 | 13 |
2023-06-17 00:59:21.616000
|
https://github.com/Jingkang50/OpenPSG
| 305 |
Panoptic scene graph generation
|
https://scholar.google.com/scholar?cluster=4427176906343613222&hl=en&as_sdt=0,5
| 6 | 2,022 |
Object-Compositional Neural Implicit Surfaces
| 22 |
eccv
| 5 | 5 |
2023-06-17 00:59:21.829000
|
https://github.com/qianyiwu/objsdf
| 157 |
Object-compositional neural implicit surfaces
|
https://scholar.google.com/scholar?cluster=9997708934654415598&hl=en&as_sdt=0,32
| 7 | 2,022 |
LiDAL: Inter-Frame Uncertainty Based Active Learning for 3D LiDAR Semantic Segmentation
| 6 |
eccv
| 2 | 0 |
2023-06-17 00:59:22.042000
|
https://github.com/hzykent/lidal
| 25 |
LiDAL: Inter-frame Uncertainty Based Active Learning for 3D LiDAR Semantic Segmentation
|
https://scholar.google.com/scholar?cluster=8461922341071305826&hl=en&as_sdt=0,5
| 3 | 2,022 |
DODA: Data-Oriented Sim-to-Real Domain Adaptation for 3D Semantic Segmentation
| 2 |
eccv
| 4 | 5 |
2023-06-17 00:59:22.255000
|
https://github.com/cvmi-lab/doda
| 40 |
DODA: Data-Oriented Sim-to-Real Domain Adaptation for 3D Semantic Segmentation
|
https://scholar.google.com/scholar?cluster=16242766710045978321&hl=en&as_sdt=0,37
| 4 | 2,022 |
TO-Scene: A Large-Scale Dataset for Understanding 3D Tabletop Scenes
| 5 |
eccv
| 5 | 0 |
2023-06-17 00:59:22.466000
|
https://github.com/GAP-LAB-CUHK-SZ/TO-Scene
| 28 |
TO-Scene: A Large-Scale Dataset for Understanding 3D Tabletop Scenes
|
https://scholar.google.com/scholar?cluster=18062236764908220812&hl=en&as_sdt=0,4
| 2 | 2,022 |
Fine-Grained Scene Graph Generation with Data Transfer
| 14 |
eccv
| 6 | 4 |
2023-06-17 00:59:22.678000
|
https://github.com/waxnkw/ietrans-sgg.pytorch
| 69 |
Fine-Grained Scene Graph Generation with Data Transfer
|
https://scholar.google.com/scholar?cluster=4124673263687372921&hl=en&as_sdt=0,25
| 1 | 2,022 |
Towards Hard-Positive Query Mining for DETR-Based Human-Object Interaction Detection
| 4 |
eccv
| 1 | 0 |
2023-06-17 00:59:22.890000
|
https://github.com/muchhair/hqm
| 25 |
Towards Hard-Positive Query Mining for DETR-Based Human-Object Interaction Detection
|
https://scholar.google.com/scholar?cluster=14859605205968905105&hl=en&as_sdt=0,5
| 1 | 2,022 |
PETR: Position Embedding Transformation for Multi-View 3D Object Detection
| 118 |
eccv
| 87 | 43 |
2023-06-17 00:59:23.102000
|
https://github.com/megvii-research/petr
| 535 |
Petr: Position embedding transformation for multi-view 3d object detection
|
https://scholar.google.com/scholar?cluster=3799744009906269739&hl=en&as_sdt=0,33
| 13 | 2,022 |
RA-Depth: Resolution Adaptive Self-Supervised Monocular Depth Estimation
| 8 |
eccv
| 4 | 8 |
2023-06-17 00:59:23.315000
|
https://github.com/hmhemu/ra-depth
| 41 |
RA-Depth: Resolution Adaptive Self-supervised Monocular Depth Estimation
|
https://scholar.google.com/scholar?cluster=10155818425251370358&hl=en&as_sdt=0,5
| 3 | 2,022 |
PolyphonicFormer: Unified Query Learning for Depth-Aware Video Panoptic Segmentation
| 15 |
eccv
| 3 | 1 |
2023-06-17 00:59:23.527000
|
https://github.com/harboryuan/polyphonicformer
| 45 |
Polyphonicformer: unified query learning for depth-aware video panoptic segmentation
|
https://scholar.google.com/scholar?cluster=7127843590064680446&hl=en&as_sdt=0,5
| 13 | 2,022 |
SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point Clouds
| 47 |
eccv
| 10 | 15 |
2023-06-17 00:59:23.739000
|
https://github.com/QingyongHu/SQN
| 83 |
Sqn: Weakly-supervised semantic segmentation of large-scale 3d point clouds
|
https://scholar.google.com/scholar?cluster=4460489745797601457&hl=en&as_sdt=0,50
| 14 | 2,022 |
3D-PL: Domain Adaptive Depth Estimation with 3D-Aware Pseudo-Labeling
| 1 |
eccv
| 1 | 3 |
2023-06-17 00:59:23.951000
|
https://github.com/ccc870206/3d-pl
| 15 |
3D-PL: Domain Adaptive Depth Estimation with 3D-Aware Pseudo-Labeling
|
https://scholar.google.com/scholar?cluster=15836829240967290716&hl=en&as_sdt=0,5
| 2 | 2,022 |
Panoptic-PartFormer: Learning a Unified Model for Panoptic Part Segmentation
| 19 |
eccv
| 2 | 2 |
2023-06-17 00:59:24.162000
|
https://github.com/lxtgh/panoptic-partformer
| 46 |
Panoptic-partformer: Learning a unified model for panoptic part segmentation
|
https://scholar.google.com/scholar?cluster=11513198882440237429&hl=en&as_sdt=0,5
| 4 | 2,022 |
Bi-PointFlowNet: Bidirectional Learning for Point Cloud Based Scene Flow Estimation
| 12 |
eccv
| 4 | 1 |
2023-06-17 00:59:24.374000
|
https://github.com/cwc1260/BiFlow
| 12 |
Bi-PointFlowNet: Bidirectional Learning for Point Cloud Based Scene Flow Estimation
|
https://scholar.google.com/scholar?cluster=12687214958834623027&hl=en&as_sdt=0,5
| 0 | 2,022 |
3DG-STFM: 3D Geometric Guided Student-Teacher Feature Matching
| 0 |
eccv
| 2 | 0 |
2023-06-17 00:59:24.586000
|
https://github.com/ryan-prime/3dg-stfm
| 27 |
3DG-STFM: 3D Geometric Guided Student-Teacher Feature Matching
|
https://scholar.google.com/scholar?cluster=15958247080770709007&hl=en&as_sdt=0,47
| 2 | 2,022 |
MonteBoxFinder: Detecting and Filtering Primitives to Fit a Noisy Point Cloud
| 1 |
eccv
| 0 | 0 |
2023-06-17 00:59:24.798000
|
https://github.com/michaelramamonjisoa/monteboxfinder
| 21 |
MonteBoxFinder: Detecting and Filtering Primitives to Fit a Noisy Point Cloud
|
https://scholar.google.com/scholar?cluster=7470902724279064123&hl=en&as_sdt=0,6
| 1 | 2,022 |
Scene Text Recognition with Permuted Autoregressive Sequence Models
| 23 |
eccv
| 85 | 26 |
2023-06-17 00:59:25.010000
|
https://github.com/baudm/parseq
| 338 |
Scene text recognition with permuted autoregressive sequence models
|
https://scholar.google.com/scholar?cluster=8935992213517493527&hl=en&as_sdt=0,26
| 12 | 2,022 |
When Counting Meets HMER: Counting-Aware Network for Handwritten Mathematical Expression Recognition
| 4 |
eccv
| 44 | 16 |
2023-06-17 00:59:25.221000
|
https://github.com/lbh1024/can
| 285 |
When Counting Meets HMER: Counting-Aware Network for Handwritten Mathematical Expression Recognition
|
https://scholar.google.com/scholar?cluster=10414110543440415468&hl=en&as_sdt=0,15
| 23 | 2,022 |
GLASS: Global to Local Attention for Scene-Text Spotting
| 7 |
eccv
| 7 | 9 |
2023-06-17 00:59:25.433000
|
https://github.com/amazon-research/glass-text-spotting
| 79 |
Glass: Global to local attention for scene-text spotting
|
https://scholar.google.com/scholar?cluster=8076622804597824484&hl=en&as_sdt=0,22
| 4 | 2,022 |
COO: Comic Onomatopoeia Dataset for Recognizing Arbitrary or Truncated Texts
| 3 |
eccv
| 1 | 0 |
2023-06-17 00:59:25.645000
|
https://github.com/ku21fan/coo-comic-onomatopoeia
| 38 |
COO: Comic Onomatopoeia Dataset for Recognizing Arbitrary or Truncated Texts
|
https://scholar.google.com/scholar?cluster=1391865788632996555&hl=en&as_sdt=0,26
| 2 | 2,022 |
Toward Understanding WordArt: Corner-Guided Transformer for Scene Text Recognition
| 4 |
eccv
| 11 | 3 |
2023-06-17 00:59:25.864000
|
https://github.com/xdxie/wordart
| 102 |
Toward Understanding WordArt: Corner-Guided Transformer for Scene Text Recognition
|
https://scholar.google.com/scholar?cluster=6406452279700529821&hl=en&as_sdt=0,5
| 4 | 2,022 |
Dynamic Low-Resolution Distillation for Cost-Efficient End-to-End Text Spotting
| 0 |
eccv
| 142 | 65 |
2023-06-17 00:59:26.076000
|
https://github.com/hikopensource/davar-lab-ocr
| 636 |
Dynamic Low-Resolution Distillation for Cost-Efficient End-to-End Text Spotting
|
https://scholar.google.com/scholar?cluster=16011258404988613521&hl=en&as_sdt=0,50
| 25 | 2,022 |
CoMER: Modeling Coverage for Transformer-Based Handwritten Mathematical Expression Recognition
| 3 |
eccv
| 13 | 8 |
2023-06-17 00:59:26.288000
|
https://github.com/Green-Wood/CoMER
| 61 |
CoMER: Modeling Coverage for Transformer-Based Handwritten Mathematical Expression Recognition
|
https://scholar.google.com/scholar?cluster=5646141492436593798&hl=en&as_sdt=0,10
| 3 | 2,022 |
Don't Forget Me: Accurate Background Recovery for Text Removal via Modeling Local-Global Context
| 2 |
eccv
| 5 | 10 |
2023-06-17 00:59:26.500000
|
https://github.com/lcy0604/ctrnet
| 50 |
Don't Forget Me: Accurate Background Recovery for Text Removal via Modeling Local-Global Context
|
https://scholar.google.com/scholar?cluster=8104354788716938084&hl=en&as_sdt=0,33
| 1 | 2,022 |
TextAdaIN: Paying Attention to Shortcut Learning in Text Recognizers
| 1 |
eccv
| 1 | 1 |
2023-06-17 00:59:26.712000
|
https://github.com/amazon-research/textadain-robust-recognition
| 19 |
TextAdaIN: Paying Attention to Shortcut Learning in Text Recognizers
|
https://scholar.google.com/scholar?cluster=11280375643907122561&hl=en&as_sdt=0,31
| 3 | 2,022 |
Multi-modal Text Recognition Networks: Interactive Enhancements between Visual and Semantic Features
| 13 |
eccv
| 6 | 0 |
2023-06-17 00:59:26.924000
|
https://github.com/wp03052/MATRN
| 56 |
Multi-modal text recognition networks: Interactive enhancements between visual and semantic features
|
https://scholar.google.com/scholar?cluster=16909271202160367665&hl=en&as_sdt=0,10
| 3 | 2,022 |
CAR: Class-Aware Regularizations for Semantic Segmentation
| 5 |
eccv
| 6 | 0 |
2023-06-17 00:59:27.136000
|
https://github.com/edwardyehuang/CAR
| 27 |
Car: Class-aware regularizations for semantic segmentation
|
https://scholar.google.com/scholar?cluster=10799908460369282649&hl=en&as_sdt=0,47
| 3 | 2,022 |
Style-Hallucinated Dual Consistency Learning for Domain Generalized Semantic Segmentation
| 10 |
eccv
| 3 | 1 |
2023-06-17 00:59:27.349000
|
https://github.com/helioszhao/shade
| 27 |
Style-hallucinated dual consistency learning for domain generalized semantic segmentation
|
https://scholar.google.com/scholar?cluster=12065305653131607870&hl=en&as_sdt=0,47
| 2 | 2,022 |
In Defense of Online Models for Video Instance Segmentation
| 35 |
eccv
| 49 | 38 |
2023-06-17 00:59:27.561000
|
https://github.com/wjf5203/vnext
| 547 |
In defense of online models for video instance segmentation
|
https://scholar.google.com/scholar?cluster=16069829188377130053&hl=en&as_sdt=0,6
| 14 | 2,022 |
Active Pointly-Supervised Instance Segmentation
| 2 |
eccv
| 0 | 0 |
2023-06-17 00:59:27.773000
|
https://github.com/chufengt/APIS
| 8 |
Active Pointly-Supervised Instance Segmentation
|
https://scholar.google.com/scholar?cluster=10978471803996868329&hl=en&as_sdt=0,25
| 1 | 2,022 |
XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model
| 48 |
eccv
| 118 | 2 |
2023-06-17 00:59:27.989000
|
https://github.com/hkchengrex/XMem
| 1,204 |
XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model
|
https://scholar.google.com/scholar?cluster=4746998901966699571&hl=en&as_sdt=0,20
| 24 | 2,022 |
2DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Clouds
| 42 |
eccv
| 40 | 24 |
2023-06-17 00:59:28.204000
|
https://github.com/yanx27/2dpass
| 306 |
2dpass: 2d priors assisted semantic segmentation on lidar point clouds
|
https://scholar.google.com/scholar?cluster=2558373953839539884&hl=en&as_sdt=0,6
| 15 | 2,022 |
Extract Free Dense Labels from CLIP
| 52 |
eccv
| 21 | 8 |
2023-06-17 00:59:28.416000
|
https://github.com/chongzhou96/maskclip
| 244 |
Extract free dense labels from clip
|
https://scholar.google.com/scholar?cluster=10784889589205919086&hl=en&as_sdt=0,44
| 7 | 2,022 |
Box-Supervised Instance Segmentation with Level Set Evolution
| 14 |
eccv
| 24 | 6 |
2023-06-17 00:59:28.628000
|
https://github.com/liwentomng/boxlevelset
| 155 |
Box-supervised instance segmentation with level set evolution
|
https://scholar.google.com/scholar?cluster=7955592219635477713&hl=en&as_sdt=0,1
| 5 | 2,022 |
Point Primitive Transformer for Long-Term 4D Point Cloud Video Understanding
| 2 |
eccv
| 0 | 1 |
2023-06-17 00:59:28.840000
|
https://github.com/hoi4d/PPTr
| 6 |
Point Primitive Transformer for Long-Term 4D Point Cloud Video Understanding
|
https://scholar.google.com/scholar?cluster=6712698866452693925&hl=en&as_sdt=0,31
| 1 | 2,022 |
TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation
| 11 |
eccv
| 3 | 2 |
2023-06-17 00:59:29.053000
|
https://github.com/damo-cv/transfgu
| 26 |
TransFGU: a top-down approach to fine-grained unsupervised semantic segmentation
|
https://scholar.google.com/scholar?cluster=8246429810533346263&hl=en&as_sdt=0,7
| 2 | 2,022 |
Cost Aggregation with 4D Convolutional Swin Transformer for Few-Shot Segmentation
| 20 |
eccv
| 14 | 1 |
2023-06-17 00:59:29.268000
|
https://github.com/Seokju-Cho/Volumetric-Aggregation-Transformer
| 129 |
Cost aggregation with 4d convolutional swin transformer for few-shot segmentation
|
https://scholar.google.com/scholar?cluster=7354076544100243051&hl=en&as_sdt=0,5
| 1 | 2,022 |
Perceptual Artifacts Localization for Inpainting
| 3 |
eccv
| 0 | 1 |
2023-06-17 00:59:29.480000
|
https://github.com/owenzlz/pal4inpaint
| 28 |
Perceptual artifacts localization for inpainting
|
https://scholar.google.com/scholar?cluster=15640327239633342238&hl=en&as_sdt=0,10
| 2 | 2,022 |
Data Efficient 3D Learner via Knowledge Transferred from 2D Model
| 2 |
eccv
| 0 | 0 |
2023-06-17 00:59:29.700000
|
https://github.com/bryanyu1997/data-efficient-3d-learner
| 15 |
Data Efficient 3D Learner via Knowledge Transferred from 2D Model
|
https://scholar.google.com/scholar?cluster=10623808226901890539&hl=en&as_sdt=0,5
| 2 | 2,022 |
Dense Gaussian Processes for Few-Shot Segmentation
| 8 |
eccv
| 3 | 1 |
2023-06-17 00:59:29.911000
|
https://github.com/joakimjohnander/dgpnet
| 41 |
Dense gaussian processes for few-shot segmentation
|
https://scholar.google.com/scholar?cluster=9696467800979236699&hl=en&as_sdt=0,34
| 2 | 2,022 |
3D Instances as 1D Kernels
| 4 |
eccv
| 4 | 1 |
2023-06-17 00:59:30.124000
|
https://github.com/w1zheng/dknet
| 45 |
3D Instances as 1D Kernels
|
https://scholar.google.com/scholar?cluster=10539575323882110234&hl=en&as_sdt=0,6
| 3 | 2,022 |
TransMatting: Enhancing Transparent Objects Matting with Transformers
| 6 |
eccv
| 2 | 1 |
2023-06-17 00:59:30.337000
|
https://github.com/acechq/transmatting
| 15 |
TransMatting: Enhancing Transparent Objects Matting with Transformers
|
https://scholar.google.com/scholar?cluster=2970412112339223847&hl=en&as_sdt=0,47
| 8 | 2,022 |
Abstracting Sketches through Simple Primitives
| 5 |
eccv
| 2 | 0 |
2023-06-17 00:59:30.549000
|
https://github.com/explainableml/sketch-primitives
| 15 |
Abstracting sketches through simple primitives
|
https://scholar.google.com/scholar?cluster=12178522811290593447&hl=en&as_sdt=0,5
| 5 | 2,022 |
Multi-Scale and Cross-Scale Contrastive Learning for Semantic Segmentation
| 1 |
eccv
| 2 | 1 |
2023-06-17 00:59:30.762000
|
https://github.com/rvimlab/ms_cs_contrseg
| 18 |
Multi-scale and Cross-scale Contrastive Learning for Semantic Segmentation
|
https://scholar.google.com/scholar?cluster=2818282965941124519&hl=en&as_sdt=0,8
| 3 | 2,022 |
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