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One-Trimap Video Matting
| 4 |
eccv
| 6 | 6 |
2023-06-17 00:59:30.985000
|
https://github.com/hongje/otvm
| 70 |
One-Trimap Video Matting
|
https://scholar.google.com/scholar?cluster=7588838291826563440&hl=en&as_sdt=0,5
| 6 | 2,022 |
D2ADA: Dynamic Density-Aware Active Domain Adaptation for Semantic Segmentation
| 1 |
eccv
| 0 | 2 |
2023-06-17 00:59:31.207000
|
https://github.com/tsunghan-wu/d2ada
| 19 |
: Dynamic Density-Aware Active Domain Adaptation for Semantic Segmentation
|
https://scholar.google.com/scholar?cluster=13096093290067916309&hl=en&as_sdt=0,5
| 2 | 2,022 |
Learning Quality-Aware Dynamic Memory for Video Object Segmentation
| 10 |
eccv
| 17 | 0 |
2023-06-17 00:59:31.451000
|
https://github.com/workforai/qdmn
| 131 |
Learning quality-aware dynamic memory for video object segmentation
|
https://scholar.google.com/scholar?cluster=14581578558335348283&hl=en&as_sdt=0,5
| 6 | 2,022 |
Learning Implicit Feature Alignment Function for Semantic Segmentation
| 14 |
eccv
| 1 | 5 |
2023-06-17 00:59:31.664000
|
https://github.com/hzhupku/ifa
| 58 |
Learning implicit feature alignment function for semantic segmentation
|
https://scholar.google.com/scholar?cluster=16350586248496262508&hl=en&as_sdt=0,5
| 3 | 2,022 |
Instance As Identity: A Generic Online Paradigm for Video Instance Segmentation
| 4 |
eccv
| 3 | 0 |
2023-06-17 00:59:31.876000
|
https://github.com/zfonemore/iai
| 16 |
Instance as identity: A generic online paradigm for video instance segmentation
|
https://scholar.google.com/scholar?cluster=2651342369418937109&hl=en&as_sdt=0,44
| 1 | 2,022 |
Geodesic-Former: A Geodesic-Guided Few-Shot 3D Point Cloud Instance Segmenter
| 2 |
eccv
| 2 | 1 |
2023-06-17 00:59:32.088000
|
https://github.com/vinairesearch/geoformer
| 14 |
Geodesic-Former: A Geodesic-Guided Few-Shot 3D Point Cloud Instance Segmenter
|
https://scholar.google.com/scholar?cluster=5545556338836437482&hl=en&as_sdt=0,19
| 3 | 2,022 |
Union-Set Multi-source Model Adaptation for Semantic Segmentation
| 2 |
eccv
| 1 | 0 |
2023-06-17 00:59:32.301000
|
https://github.com/lzy7976/union-set-model-adaptation
| 9 |
Union-Set Multi-source Model Adaptation for Semantic Segmentation
|
https://scholar.google.com/scholar?cluster=8783974652276072046&hl=en&as_sdt=0,5
| 2 | 2,022 |
SPSN: Superpixel Prototype Sampling Network for RGB-D Salient Object Detection
| 19 |
eccv
| 3 | 1 |
2023-06-17 00:59:32.513000
|
https://github.com/Hydragon516/SPSN
| 32 |
Spsn: Superpixel prototype sampling network for rgb-d salient object detection
|
https://scholar.google.com/scholar?cluster=961197252690730583&hl=en&as_sdt=0,5
| 2 | 2,022 |
Global Spectral Filter Memory Network for Video Object Segmentation
| 8 |
eccv
| 2 | 1 |
2023-06-17 00:59:32.727000
|
https://github.com/workforai/gsfm
| 29 |
Global spectral filter memory network for video object segmentation
|
https://scholar.google.com/scholar?cluster=6531040020135946124&hl=en&as_sdt=0,47
| 3 | 2,022 |
Video Instance Segmentation via Multi-Scale Spatio-Temporal Split Attention Transformer
| 6 |
eccv
| 2 | 3 |
2023-06-17 00:59:32.946000
|
https://github.com/OmkarThawakar/MSSTS-VIS
| 36 |
Video Instance Segmentation via Multi-Scale Spatio-Temporal Split Attention Transformer
|
https://scholar.google.com/scholar?cluster=971651369893003442&hl=en&as_sdt=0,23
| 8 | 2,022 |
Learning Topological Interactions for Multi-Class Medical Image Segmentation
| 5 |
eccv
| 5 | 0 |
2023-06-17 00:59:33.162000
|
https://github.com/topoxlab/topointeraction
| 53 |
Learning Topological Interactions for Multi-Class Medical Image Segmentation
|
https://scholar.google.com/scholar?cluster=7636749497701353644&hl=en&as_sdt=0,30
| 4 | 2,022 |
Unsupervised Segmentation in Real-World Images via Spelke Object Inference
| 8 |
eccv
| 2 | 4 |
2023-06-17 00:59:33.382000
|
https://github.com/neuroailab/eisen
| 20 |
Unsupervised segmentation in real-world images via spelke object inference
|
https://scholar.google.com/scholar?cluster=17744200822268427620&hl=en&as_sdt=0,5
| 4 | 2,022 |
A Simple Baseline for Open-Vocabulary Semantic Segmentation with Pre-trained Vision-Language Model
| 23 |
eccv
| 10 | 6 |
2023-06-17 00:59:33.594000
|
https://github.com/mendelxu/zsseg.baseline
| 126 |
A Simple Baseline for Open-Vocabulary Semantic Segmentation with Pre-trained Vision-Language Model
|
https://scholar.google.com/scholar?cluster=1990243593035555434&hl=en&as_sdt=0,5
| 5 | 2,022 |
Generative Subgraph Contrast for Self-Supervised Graph Representation Learning
| 1 |
eccv
| 1 | 0 |
2023-06-17 00:59:33.808000
|
https://github.com/yh-han/gsc
| 11 |
Generative Subgraph Contrast for Self-Supervised Graph Representation Learning
|
https://scholar.google.com/scholar?cluster=17324044096784760749&hl=en&as_sdt=0,26
| 1 | 2,022 |
SdAE: Self-Distillated Masked Autoencoder
| 18 |
eccv
| 1 | 2 |
2023-06-17 00:59:34.020000
|
https://github.com/abrahamyabo/sdae
| 36 |
Sdae: Self-distillated masked autoencoder
|
https://scholar.google.com/scholar?cluster=6427547624181496716&hl=en&as_sdt=0,5
| 4 | 2,022 |
Concurrent Subsidiary Supervision for Unsupervised Source-Free Domain Adaptation
| 7 |
eccv
| 2 | 0 |
2023-06-17 00:59:34.232000
|
https://github.com/val-iisc/stickerda
| 17 |
Concurrent subsidiary supervision for unsupervised source-free domain adaptation
|
https://scholar.google.com/scholar?cluster=16781913863489916282&hl=en&as_sdt=0,5
| 12 | 2,022 |
Active Learning Strategies for Weakly-Supervised Object Detection
| 3 |
eccv
| 5 | 1 |
2023-06-17 00:59:34.445000
|
https://github.com/huyvvo/bib
| 25 |
Active Learning Strategies for Weakly-Supervised Object Detection
|
https://scholar.google.com/scholar?cluster=6555341052977464243&hl=en&as_sdt=0,5
| 2 | 2,022 |
Mc-BEiT: Multi-Choice Discretization for Image BERT Pre-training
| 18 |
eccv
| 1 | 0 |
2023-06-17 00:59:34.656000
|
https://github.com/lixiaotong97/mc-beit
| 21 |
mc-BEiT: Multi-choice Discretization for Image BERT Pre-training
|
https://scholar.google.com/scholar?cluster=10612926957976727479&hl=en&as_sdt=0,5
| 2 | 2,022 |
Bootstrapped Masked Autoencoders for Vision BERT Pretraining
| 18 |
eccv
| 6 | 0 |
2023-06-17 00:59:34.868000
|
https://github.com/lightdxy/bootmae
| 90 |
Bootstrapped Masked Autoencoders for Vision BERT Pretraining
|
https://scholar.google.com/scholar?cluster=11908913569029309505&hl=en&as_sdt=0,10
| 3 | 2,022 |
What to Hide from Your Students: Attention-Guided Masked Image Modeling
| 36 |
eccv
| 4 | 0 |
2023-06-17 00:59:35.089000
|
https://github.com/gkakogeorgiou/attmask
| 31 |
What to hide from your students: Attention-guided masked image modeling
|
https://scholar.google.com/scholar?cluster=13621702207944750833&hl=en&as_sdt=0,5
| 5 | 2,022 |
Pointly-Supervised Panoptic Segmentation
| 5 |
eccv
| 1 | 1 |
2023-06-17 00:59:35.307000
|
https://github.com/bravegroup/psps
| 19 |
Pointly-Supervised Panoptic Segmentation
|
https://scholar.google.com/scholar?cluster=14167808655489374713&hl=en&as_sdt=0,1
| 4 | 2,022 |
HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation
| 43 |
eccv
| 25 | 4 |
2023-06-17 00:59:35.524000
|
https://github.com/lhoyer/hrda
| 188 |
HRDA: Context-aware high-resolution domain-adaptive semantic segmentation
|
https://scholar.google.com/scholar?cluster=11500016484284904863&hl=en&as_sdt=0,5
| 5 | 2,022 |
Unsupervised Selective Labeling for More Effective Semi-Supervised Learning
| 6 |
eccv
| 3 | 1 |
2023-06-17 00:59:35.760000
|
https://github.com/TonyLianLong/UnsupervisedSelectiveLabeling
| 27 |
Unsupervised Selective Labeling for More Effective Semi-Supervised Learning
|
https://scholar.google.com/scholar?cluster=2772643387348706767&hl=en&as_sdt=0,28
| 2 | 2,022 |
Max Pooling with Vision Transformers Reconciles Class and Shape in Weakly Supervised Semantic Segmentation
| 10 |
eccv
| 1 | 0 |
2023-06-17 00:59:36.028000
|
https://github.com/deepplants/vit-pcm
| 14 |
Max Pooling with Vision Transformers reconciles class and shape in weakly supervised semantic segmentation
|
https://scholar.google.com/scholar?cluster=13877065122591623844&hl=en&as_sdt=0,5
| 2 | 2,022 |
Dense Siamese Network for Dense Unsupervised Learning
| 4 |
eccv
| 2 | 0 |
2023-06-17 00:59:36.298000
|
https://github.com/zwwwayne/densesiam
| 26 |
Dense Siamese Network for Dense Unsupervised Learning
|
https://scholar.google.com/scholar?cluster=2962540697381771652&hl=en&as_sdt=0,25
| 1 | 2,022 |
Multi-Granularity Distillation Scheme towards Lightweight Semi-Supervised Semantic Segmentation
| 2 |
eccv
| 1 | 3 |
2023-06-17 00:59:36.510000
|
https://github.com/jayqine/mgd-ssss
| 11 |
Multi-granularity Distillation Scheme Towards Lightweight Semi-supervised Semantic Segmentation
|
https://scholar.google.com/scholar?cluster=14826363507378603600&hl=en&as_sdt=0,47
| 3 | 2,022 |
CP2: Copy-Paste Contrastive Pretraining for Semantic Segmentation
| 10 |
eccv
| 1 | 0 |
2023-06-17 00:59:36.723000
|
https://github.com/wangf3014/cp2
| 6 |
CP: Copy-Paste Contrastive Pretraining for Semantic Segmentation
|
https://scholar.google.com/scholar?cluster=9077524711445116563&hl=en&as_sdt=0,5
| 1 | 2,022 |
Self-Filtering: A Noise-Aware Sample Selection for Label Noise with Confidence Penalization
| 7 |
eccv
| 2 | 0 |
2023-06-17 00:59:36.934000
|
https://github.com/1998v7/self-filtering
| 19 |
Self-Filtering: A Noise-Aware Sample Selection for Label Noise with Confidence Penalization
|
https://scholar.google.com/scholar?cluster=11503343963876701921&hl=en&as_sdt=0,36
| 1 | 2,022 |
RDA: Reciprocal Distribution Alignment for Robust Semi-Supervised Learning
| 1 |
eccv
| 0 | 0 |
2023-06-17 00:59:37.155000
|
https://github.com/njuyued/rda4robustssl
| 7 |
RDA: Reciprocal Distribution Alignment for Robust Semi-supervised Learning
|
https://scholar.google.com/scholar?cluster=1893818676204532459&hl=en&as_sdt=0,11
| 1 | 2,022 |
MemSAC: Memory Augmented Sample Consistency for Large Scale Domain Adaptation
| 1 |
eccv
| 0 | 0 |
2023-06-17 00:59:37.368000
|
https://github.com/ViLab-UCSD/MemSAC_ECCV2022
| 6 |
MemSAC: Memory Augmented Sample Consistency for Large Scale Domain Adaptation
|
https://scholar.google.com/scholar?cluster=17292964986746280650&hl=en&as_sdt=0,5
| 2 | 2,022 |
Synergistic Self-Supervised and Quantization Learning
| 2 |
eccv
| 4 | 0 |
2023-06-17 00:59:37.583000
|
https://github.com/megvii-research/ssql-eccv2022
| 67 |
Synergistic Self-supervised and Quantization Learning
|
https://scholar.google.com/scholar?cluster=3701150918575417216&hl=en&as_sdt=0,23
| 4 | 2,022 |
Semi-Supervised Vision Transformers
| 14 |
eccv
| 5 | 1 |
2023-06-17 00:59:37.798000
|
https://github.com/wengzejia1/semiformer
| 26 |
Semi-supervised vision transformers
|
https://scholar.google.com/scholar?cluster=83081748366699225&hl=en&as_sdt=0,5
| 3 | 2,022 |
Domain Adaptive Video Segmentation via Temporal Pseudo Supervision
| 5 |
eccv
| 6 | 9 |
2023-06-17 00:59:38.011000
|
https://github.com/xing0047/tps
| 28 |
Domain adaptive video segmentation via temporal pseudo supervision
|
https://scholar.google.com/scholar?cluster=7231098623956259110&hl=en&as_sdt=0,5
| 2 | 2,022 |
ConMatch: Semi-Supervised Learning with Confidence-Guided Consistency Regularization
| 6 |
eccv
| 3 | 1 |
2023-06-17 00:59:38.224000
|
https://github.com/jiwoncocoder/conmatch
| 24 |
Conmatch: Semi-supervised learning with confidence-guided consistency regularization
|
https://scholar.google.com/scholar?cluster=23511256883904024&hl=en&as_sdt=0,10
| 4 | 2,022 |
FedX: Unsupervised Federated Learning with Cross Knowledge Distillation
| 6 |
eccv
| 6 | 0 |
2023-06-17 00:59:38.436000
|
https://github.com/sungwon-han/fedx
| 47 |
FedX: Unsupervised Federated Learning with Cross Knowledge Distillation
|
https://scholar.google.com/scholar?cluster=15024670483115601107&hl=en&as_sdt=0,44
| 3 | 2,022 |
Decoupled Adversarial Contrastive Learning for Self-Supervised Adversarial Robustness
| 6 |
eccv
| 1 | 1 |
2023-06-17 00:59:38.649000
|
https://github.com/pantheon5100/deacl
| 12 |
Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial Robustness
|
https://scholar.google.com/scholar?cluster=33793130511872188&hl=en&as_sdt=0,23
| 3 | 2,022 |
GOCA: Guided Online Cluster Assignment for Self-Supervised Video Representation Learning
| 2 |
eccv
| 1 | 1 |
2023-06-17 00:59:38.861000
|
https://github.com/seleucia/goca
| 7 |
GOCA: guided online cluster assignment for self-supervised video representation Learning
|
https://scholar.google.com/scholar?cluster=11832380063761473468&hl=en&as_sdt=0,47
| 1 | 2,022 |
Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning
| 1 |
eccv
| 2 | 0 |
2023-06-17 00:59:39.074000
|
https://github.com/ucdvision/cmsf
| 5 |
Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning
|
https://scholar.google.com/scholar?cluster=3423733438227857877&hl=en&as_sdt=0,5
| 3 | 2,022 |
Revisiting the Critical Factors of Augmentation-Invariant Representation Learning
| 3 |
eccv
| 0 | 0 |
2023-06-17 00:59:39.287000
|
https://github.com/megvii-research/revisitairl
| 11 |
Revisiting the Critical Factors of Augmentation-Invariant Representation Learning
|
https://scholar.google.com/scholar?cluster=5620391103702962878&hl=en&as_sdt=0,33
| 3 | 2,022 |
CA-SSL: Class-Agnostic Semi-Supervised Learning for Detection and Segmentation
| 2 |
eccv
| 42 | 19 |
2023-06-17 00:59:39.498000
|
https://github.com/dvlab-research/Entity
| 449 |
CA-SSL: Class-Agnostic Semi-Supervised Learning for Detection and Segmentation
|
https://scholar.google.com/scholar?cluster=9702778436571703527&hl=en&as_sdt=0,31
| 20 | 2,022 |
Semantic-Aware Fine-Grained Correspondence
| 2 |
eccv
| 1 | 1 |
2023-06-17 00:59:39.710000
|
https://github.com/alxead/sfc
| 13 |
Semantic-Aware Fine-Grained Correspondence
|
https://scholar.google.com/scholar?cluster=9515469045960583745&hl=en&as_sdt=0,14
| 1 | 2,022 |
Self-Supervised Classification Network
| 15 |
eccv
| 4 | 0 |
2023-06-17 00:59:39.924000
|
https://github.com/elad-amrani/self-classifier
| 31 |
Self-supervised classification network
|
https://scholar.google.com/scholar?cluster=12911109870349597402&hl=en&as_sdt=0,31
| 1 | 2,022 |
Semi-Supervised Object Detection via Virtual Category Learning
| 5 |
eccv
| 0 | 0 |
2023-06-17 00:59:40.135000
|
https://github.com/geoffreychen777/vc
| 6 |
Semi-supervised object detection via virtual category learning
|
https://scholar.google.com/scholar?cluster=12705891433611100689&hl=en&as_sdt=0,10
| 1 | 2,022 |
Completely Self-Supervised Crowd Counting via Distribution Matching
| 7 |
eccv
| 8 | 1 |
2023-06-17 00:59:40.348000
|
https://github.com/val-iisc/css-ccnn
| 25 |
Completely self-supervised crowd counting via distribution matching
|
https://scholar.google.com/scholar?cluster=15996947716561762009&hl=en&as_sdt=0,5
| 14 | 2,022 |
Coarse-to-Fine Incremental Few-Shot Learning
| 4 |
eccv
| 0 | 0 |
2023-06-17 00:59:40.561000
|
https://github.com/HAIV-Lab/Knowe
| 4 |
Coarse-to-fine incremental few-shot learning
|
https://scholar.google.com/scholar?cluster=15208517894348282835&hl=en&as_sdt=0,5
| 0 | 2,022 |
Learning Unbiased Transferability for Domain Adaptation by Uncertainty Modeling
| 0 |
eccv
| 1 | 0 |
2023-06-17 00:59:40.774000
|
https://github.com/puchapu/utep
| 2 |
Learning Unbiased Transferability for Domain Adaptation by Uncertainty Modeling
|
https://scholar.google.com/scholar?cluster=10772316129311859971&hl=en&as_sdt=0,5
| 1 | 2,022 |
CYBORGS: Contrastively Bootstrapping Object Representations by Grounding in Segmentation
| 2 |
eccv
| 0 | 1 |
2023-06-17 00:59:40.986000
|
https://github.com/renwang435/cyborgs
| 3 |
Cyborgs: Contrastively bootstrapping object representations by grounding in segmentation
|
https://scholar.google.com/scholar?cluster=4093202168544509121&hl=en&as_sdt=0,5
| 2 | 2,022 |
Object Discovery via Contrastive Learning for Weakly Supervised Object Detection
| 4 |
eccv
| 4 | 4 |
2023-06-17 00:59:41.207000
|
https://github.com/jinhseo/od-wscl
| 31 |
Object Discovery via Contrastive Learning for Weakly Supervised Object Detection
|
https://scholar.google.com/scholar?cluster=4274032166116217116&hl=en&as_sdt=0,5
| 1 | 2,022 |
Semi-Leak: Membership Inference Attacks against Semi-Supervised Learning
| 3 |
eccv
| 0 | 0 |
2023-06-17 00:59:41.420000
|
https://github.com/xinleihe/semi-leak
| 9 |
Semi-Leak: Membership Inference Attacks Against Semi-supervised Learning
|
https://scholar.google.com/scholar?cluster=9233507844643867685&hl=en&as_sdt=0,5
| 1 | 2,022 |
OpenLDN: Learning to Discover Novel Classes for Open-World Semi-Supervised Learning
| 7 |
eccv
| 4 | 3 |
2023-06-17 00:59:41.632000
|
https://github.com/nayeemrizve/openldn
| 23 |
Openldn: Learning to discover novel classes for open-world semi-supervised learning
|
https://scholar.google.com/scholar?cluster=12710236080905969514&hl=en&as_sdt=0,5
| 1 | 2,022 |
Embedding Contrastive Unsupervised Features to Cluster in- and Out-of-Distribution Noise in Corrupted Image Datasets
| 2 |
eccv
| 0 | 1 |
2023-06-17 00:59:41.845000
|
https://github.com/paulalbert31/sncf
| 9 |
Embedding contrastive unsupervised features to cluster in-and out-of-distribution noise in corrupted image datasets
|
https://scholar.google.com/scholar?cluster=6052251975448117268&hl=en&as_sdt=0,26
| 2 | 2,022 |
Towards Realistic Semi-Supervised Learning
| 8 |
eccv
| 1 | 3 |
2023-06-17 00:59:42.058000
|
https://github.com/nayeemrizve/trssl
| 24 |
Towards realistic semi-supervised learning
|
https://scholar.google.com/scholar?cluster=15906626340629740128&hl=en&as_sdt=0,5
| 1 | 2,022 |
Masked Siamese Networks for Label-Efficient Learning
| 99 |
eccv
| 30 | 16 |
2023-06-17 00:59:42.271000
|
https://github.com/facebookresearch/msn
| 400 |
Masked siamese networks for label-efficient learning
|
https://scholar.google.com/scholar?cluster=9235835052951341282&hl=en&as_sdt=0,23
| 13 | 2,022 |
Natural Synthetic Anomalies for Self-Supervised Anomaly Detection and Localization
| 17 |
eccv
| 5 | 1 |
2023-06-17 00:59:42.483000
|
https://github.com/hmsch/natural-synthetic-anomalies
| 29 |
Natural synthetic anomalies for self-supervised anomaly detection and localization
|
https://scholar.google.com/scholar?cluster=7248162955817269145&hl=en&as_sdt=0,5
| 2 | 2,022 |
Understanding Collapse in Non-Contrastive Siamese Representation Learning
| 10 |
eccv
| 1 | 1 |
2023-06-17 00:59:42.695000
|
https://github.com/alexlioralexli/noncontrastive-ssl
| 4 |
Understanding Collapse in Non-contrastive Siamese Representation Learning
|
https://scholar.google.com/scholar?cluster=1641172093663463753&hl=en&as_sdt=0,44
| 1 | 2,022 |
Federated Self-Supervised Learning for Video Understanding
| 2 |
eccv
| 1 | 0 |
2023-06-17 00:59:42.908000
|
https://github.com/yasar-rehman/fedvssl
| 15 |
Federated Self-supervised Learning for Video Understanding
|
https://scholar.google.com/scholar?cluster=5203922739716905699&hl=en&as_sdt=0,4
| 6 | 2,022 |
Towards Efficient and Effective Self-Supervised Learning of Visual Representations
| 3 |
eccv
| 1 | 0 |
2023-06-17 00:59:43.120000
|
https://github.com/val-iisc/effssl
| 4 |
Towards Efficient and Effective Self-Supervised Learning of Visual Representations
|
https://scholar.google.com/scholar?cluster=9102827506777394507&hl=en&as_sdt=0,44
| 13 | 2,022 |
MVSTER: Epipolar Transformer for Efficient Multi-View Stereo
| 20 |
eccv
| 12 | 10 |
2023-06-17 00:59:43.333000
|
https://github.com/jeffwang987/mvster
| 149 |
MVSTER: epipolar transformer for efficient multi-view stereo
|
https://scholar.google.com/scholar?cluster=16748508301109808969&hl=en&as_sdt=0,5
| 6 | 2,022 |
RC-MVSNet: Unsupervised Multi-View Stereo with Neural Rendering
| 10 |
eccv
| 13 | 7 |
2023-06-17 00:59:43.545000
|
https://github.com/boese0601/rc-mvsnet
| 173 |
RC-MVSNet: unsupervised multi-view stereo with neural rendering
|
https://scholar.google.com/scholar?cluster=7214458458085402585&hl=en&as_sdt=0,22
| 17 | 2,022 |
ARF: Artistic Radiance Fields
| 30 |
eccv
| 41 | 7 |
2023-06-17 00:59:43.758000
|
https://github.com/Kai-46/ARF-svox2
| 435 |
Arf: Artistic radiance fields
|
https://scholar.google.com/scholar?cluster=9612416165197735153&hl=en&as_sdt=0,16
| 18 | 2,022 |
Multiview Stereo with Cascaded Epipolar RAFT
| 5 |
eccv
| 9 | 4 |
2023-06-17 00:59:43.970000
|
https://github.com/princeton-vl/cer-mvs
| 100 |
Multiview stereo with cascaded epipolar raft
|
https://scholar.google.com/scholar?cluster=5026889917906841246&hl=en&as_sdt=0,43
| 9 | 2,022 |
ASpanFormer: Detector-Free Image Matching with Adaptive Span Transformer
| 27 |
eccv
| 16 | 0 |
2023-06-17 00:59:44.241000
|
https://github.com/apple/ml-aspanformer
| 100 |
Aspanformer: Detector-free image matching with adaptive span transformer
|
https://scholar.google.com/scholar?cluster=4389376922954725361&hl=en&as_sdt=0,37
| 12 | 2,022 |
NDF: Neural Deformable Fields for Dynamic Human Modelling
| 4 |
eccv
| 4 | 1 |
2023-06-17 00:59:44.453000
|
https://github.com/hkbu-vscomputing/2022_eccv_ndf
| 14 |
NDF: Neural Deformable Fields for Dynamic Human Modelling
|
https://scholar.google.com/scholar?cluster=10897766450583864581&hl=en&as_sdt=0,5
| 1 | 2,022 |
Neural Density-Distance Fields
| 5 |
eccv
| 8 | 3 |
2023-06-17 00:59:44.665000
|
https://github.com/ueda0319/neddf
| 203 |
Neural Density-Distance Fields
|
https://scholar.google.com/scholar?cluster=10169858113129806585&hl=en&as_sdt=0,5
| 13 | 2,022 |
Learning Online Multi-sensor Depth Fusion
| 1 |
eccv
| 0 | 0 |
2023-06-17 00:59:44.878000
|
https://github.com/tfy14esa/senfunet
| 7 |
Learning online multi-sensor depth fusion
|
https://scholar.google.com/scholar?cluster=12133624018619212262&hl=en&as_sdt=0,43
| 2 | 2,022 |
Improving RGB-D Point Cloud Registration by Learning Multi-Scale Local Linear Transformation
| 1 |
eccv
| 0 | 0 |
2023-06-17 00:59:45.090000
|
https://github.com/514dna/llt
| 11 |
Improving rgb-d point cloud registration by learning multi-scale local linear transformation
|
https://scholar.google.com/scholar?cluster=467163058867525578&hl=en&as_sdt=0,5
| 3 | 2,022 |
Real-Time Neural Character Rendering with Pose-Guided Multiplane Images
| 6 |
eccv
| 5 | 1 |
2023-06-17 00:59:45.303000
|
https://github.com/ken-ouyang/PGMPI
| 46 |
Real-time neural character rendering with pose-guided multiplane images
|
https://scholar.google.com/scholar?cluster=9080153091759921402&hl=en&as_sdt=0,5
| 3 | 2,022 |
Disentangling Object Motion and Occlusion for Unsupervised Multi-Frame Monocular Depth
| 7 |
eccv
| 8 | 5 |
2023-06-17 00:59:45.514000
|
https://github.com/AutoAILab/DynamicDepth
| 96 |
Disentangling Object Motion and Occlusion for Unsupervised Multi-frame Monocular Depth
|
https://scholar.google.com/scholar?cluster=7095473850872719452&hl=en&as_sdt=0,5
| 3 | 2,022 |
Context-Enhanced Stereo Transformer
| 2 |
eccv
| 3 | 3 |
2023-06-17 00:59:45.727000
|
https://github.com/guoweiyu/context-enhanced-stereo-transformer
| 30 |
Context-Enhanced Stereo Transformer
|
https://scholar.google.com/scholar?cluster=3543640163219156828&hl=en&as_sdt=0,25
| 1 | 2,022 |
Gen6D: Generalizable Model-Free 6-DoF Object Pose Estimation from RGB Images
| 9 |
eccv
| 50 | 56 |
2023-06-17 00:59:45.940000
|
https://github.com/liuyuan-pal/gen6d
| 395 |
Gen6D: Generalizable model-free 6-DoF object pose estimation from RGB images
|
https://scholar.google.com/scholar?cluster=5099493959917547229&hl=en&as_sdt=0,42
| 9 | 2,022 |
Latency-Aware Collaborative Perception
| 20 |
eccv
| 1 | 2 |
2023-06-17 00:59:46.152000
|
https://github.com/mediabrain-sjtu/syncnet
| 13 |
Latency-aware collaborative perception
|
https://scholar.google.com/scholar?cluster=12080385681051469958&hl=en&as_sdt=0,5
| 0 | 2,022 |
TensoRF: Tensorial Radiance Fields
| 230 |
eccv
| 126 | 45 |
2023-06-17 00:59:46.364000
|
https://github.com/apchenstu/TensoRF
| 898 |
Tensorf: Tensorial radiance fields
|
https://scholar.google.com/scholar?cluster=9392347583762409161&hl=en&as_sdt=0,29
| 20 | 2,022 |
NeFSAC: Neurally Filtered Minimal Samples
| 5 |
eccv
| 1 | 1 |
2023-06-17 00:59:46.576000
|
https://github.com/cavalli1234/nefsac
| 36 |
NeFSAC: neurally filtered minimal samples
|
https://scholar.google.com/scholar?cluster=13860320733798826375&hl=en&as_sdt=0,5
| 6 | 2,022 |
HDR-Plenoxels: Self-Calibrating High Dynamic Range Radiance Fields
| 4 |
eccv
| 7 | 3 |
2023-06-17 00:59:46.788000
|
https://github.com/postech-ami/hdr-plenoxels
| 90 |
HDR-Plenoxels: Self-Calibrating High Dynamic Range Radiance Fields
|
https://scholar.google.com/scholar?cluster=13393942085458083922&hl=en&as_sdt=0,39
| 9 | 2,022 |
NeuMan: Neural Human Radiance Field from a Single Video
| 43 |
eccv
| 135 | 38 |
2023-06-17 00:59:47
|
https://github.com/apple/ml-neuman
| 1,096 |
Neuman: Neural human radiance field from a single video
|
https://scholar.google.com/scholar?cluster=4308511704577688456&hl=en&as_sdt=0,5
| 35 | 2,022 |
TAVA: Template-Free Animatable Volumetric Actors
| 33 |
eccv
| 16 | 1 |
2023-06-17 00:59:47.217000
|
https://github.com/facebookresearch/tava
| 179 |
Tava: Template-free animatable volumetric actors
|
https://scholar.google.com/scholar?cluster=7969304324450759992&hl=en&as_sdt=0,29
| 12 | 2,022 |
EASNet: Searching Elastic and Accurate Network Architecture for Stereo Matching
| 2 |
eccv
| 0 | 0 |
2023-06-17 00:59:47.430000
|
https://github.com/hkbu-hpml/easnet
| 6 |
EASNet: Searching Elastic and Accurate Network Architecture for Stereo Matching
|
https://scholar.google.com/scholar?cluster=15435889328607570391&hl=en&as_sdt=0,5
| 1 | 2,022 |
ParticleSfM: Exploiting Dense Point Trajectories for Localizing Moving Cameras in the Wild
| 5 |
eccv
| 15 | 3 |
2023-06-17 00:59:47.642000
|
https://github.com/bytedance/particle-sfm
| 160 |
ParticleSfM: Exploiting Dense Point Trajectories for Localizing Moving Cameras in the Wild
|
https://scholar.google.com/scholar?cluster=649075297016253795&hl=en&as_sdt=0,5
| 14 | 2,022 |
Approximate Differentiable Rendering with Algebraic Surfaces
| 2 |
eccv
| 2 | 2 |
2023-06-17 00:59:47.855000
|
https://github.com/leonidk/fuzzy-metaballs
| 48 |
Approximate Differentiable Rendering with Algebraic Surfaces
|
https://scholar.google.com/scholar?cluster=14972940426953053796&hl=en&as_sdt=0,5
| 3 | 2,022 |
GraphFit: Learning Multi-Scale Graph-Convolutional Representation for Point Cloud Normal Estimation
| 4 |
eccv
| 2 | 0 |
2023-06-17 00:59:48.069000
|
https://github.com/uestcjay/graphfit
| 21 |
GraphFit: Learning Multi-scale Graph-Convolutional Representation for Point Cloud Normal Estimation
|
https://scholar.google.com/scholar?cluster=13505484244080411576&hl=en&as_sdt=0,38
| 1 | 2,022 |
Point Scene Understanding via Disentangled Instance Mesh Reconstruction
| 6 |
eccv
| 3 | 4 |
2023-06-17 00:59:48.281000
|
https://github.com/ashawkey/dimr
| 25 |
Point scene understanding via disentangled instance mesh reconstruction
|
https://scholar.google.com/scholar?cluster=2693964574751110058&hl=en&as_sdt=0,5
| 5 | 2,022 |
Space-Partitioning RANSAC
| 3 |
eccv
| 79 | 7 |
2023-06-17 00:59:48.493000
|
https://github.com/danini/graph-cut-ransac
| 335 |
Space-Partitioning RANSAC
|
https://scholar.google.com/scholar?cluster=7758768906343068839&hl=en&as_sdt=0,33
| 21 | 2,022 |
What Matters for 3D Scene Flow Network
| 10 |
eccv
| 4 | 3 |
2023-06-17 00:59:48.705000
|
https://github.com/irmvlab/3dflow
| 36 |
What Matters for 3D Scene Flow Network
|
https://scholar.google.com/scholar?cluster=15648120699613324906&hl=en&as_sdt=0,31
| 2 | 2,022 |
GraphCSPN: Geometry-Aware Depth Completion via Dynamic GCNs
| 3 |
eccv
| 1 | 3 |
2023-06-17 00:59:48.918000
|
https://github.com/xinliu20/graphcspn_eccv2022
| 15 |
GraphCSPN: Geometry-Aware Depth Completion via Dynamic GCNs
|
https://scholar.google.com/scholar?cluster=1840962488966960353&hl=en&as_sdt=0,43
| 2 | 2,022 |
Language-Grounded Indoor 3D Semantic Segmentation in the Wild
| 5 |
eccv
| 14 | 1 |
2023-06-17 00:59:49.130000
|
https://github.com/RozDavid/LanguageGroundedSemseg
| 77 |
Language-grounded indoor 3D semantic segmentation in the wild
|
https://scholar.google.com/scholar?cluster=4523012745679704845&hl=en&as_sdt=0,47
| 4 | 2,022 |
FLEX: Extrinsic Parameters-Free Multi-View 3D Human Motion Reconstruction
| 7 |
eccv
| 4 | 10 |
2023-06-17 00:59:49.342000
|
https://github.com/BrianG13/FLEX
| 37 |
FLEX: Extrinsic Parameters-free Multi-view 3D Human Motion Reconstruction
|
https://scholar.google.com/scholar?cluster=9329272626865528352&hl=en&as_sdt=0,47
| 8 | 2,022 |
ActiveNeRF: Learning Where to See with Uncertainty Estimation
| 7 |
eccv
| 3 | 4 |
2023-06-17 00:59:49.554000
|
https://github.com/leaplabthu/activenerf
| 58 |
ActiveNeRF: Learning Where to See with Uncertainty Estimation
|
https://scholar.google.com/scholar?cluster=7696752785009743824&hl=en&as_sdt=0,5
| 6 | 2,022 |
PoserNet: Refining Relative Camera Poses Exploiting Object Detections
| 1 |
eccv
| 0 | 0 |
2023-06-17 00:59:49.766000
|
https://github.com/iit-pavis/posernet
| 40 |
PoserNet: Refining Relative Camera Poses Exploiting Object Detections
|
https://scholar.google.com/scholar?cluster=5415819577360667082&hl=en&as_sdt=0,39
| 6 | 2,022 |
Class-Incremental Novel Class Discovery
| 9 |
eccv
| 6 | 2 |
2023-06-17 00:59:49.980000
|
https://github.com/oatmealliu/class-incd
| 55 |
Class-incremental Novel Class Discovery
|
https://scholar.google.com/scholar?cluster=16320430811292329479&hl=en&as_sdt=0,5
| 4 | 2,022 |
Prototype-Guided Continual Adaptation for Class-Incremental Unsupervised Domain Adaptation
| 7 |
eccv
| 1 | 1 |
2023-06-17 00:59:50.223000
|
https://github.com/hongbin98/proca
| 20 |
Prototype-guided continual adaptation for class-incremental unsupervised domain adaptation
|
https://scholar.google.com/scholar?cluster=8804941606286373494&hl=en&as_sdt=0,39
| 3 | 2,022 |
DecoupleNet: Decoupled Network for Domain Adaptive Semantic Segmentation
| 17 |
eccv
| 2 | 0 |
2023-06-17 00:59:50.436000
|
https://github.com/dvlab-research/decouplenet
| 30 |
DecoupleNet: Decoupled network for domain adaptive semantic segmentation
|
https://scholar.google.com/scholar?cluster=9009915321489245170&hl=en&as_sdt=0,5
| 3 | 2,022 |
Mind the Gap in Distilling StyleGANs
| 4 |
eccv
| 1 | 3 |
2023-06-17 00:59:50.647000
|
https://github.com/xuguodong03/stylekd
| 22 |
Mind the Gap in Distilling StyleGANs
|
https://scholar.google.com/scholar?cluster=5377121854905583705&hl=en&as_sdt=0,47
| 7 | 2,022 |
Long-Tailed Class Incremental Learning
| 2 |
eccv
| 0 | 0 |
2023-06-17 00:59:50.859000
|
https://github.com/xialeiliu/long-tailed-cil
| 26 |
Long-Tailed Class Incremental Learning
|
https://scholar.google.com/scholar?cluster=9618483384480829027&hl=en&as_sdt=0,14
| 6 | 2,022 |
GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation
| 5 |
eccv
| 1 | 0 |
2023-06-17 00:59:51.071000
|
https://github.com/saltoricristiano/gipso-sfouda
| 31 |
GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation
|
https://scholar.google.com/scholar?cluster=13813760731976228346&hl=en&as_sdt=0,33
| 6 | 2,022 |
CoSMix: Compositional Semantic Mix for Domain Adaptation in 3D LiDAR Segmentation
| 17 |
eccv
| 5 | 0 |
2023-06-17 00:59:51.284000
|
https://github.com/saltoricristiano/cosmix-uda
| 40 |
Cosmix: Compositional semantic mix for domain adaptation in 3d lidar segmentation
|
https://scholar.google.com/scholar?cluster=6786759772054921592&hl=en&as_sdt=0,5
| 6 | 2,022 |
A Unified Framework for Domain Adaptive Pose Estimation
| 9 |
eccv
| 4 | 1 |
2023-06-17 00:59:51.496000
|
https://github.com/visionlearninggroup/uda_poseestimation
| 11 |
A unified framework for domain adaptive pose estimation
|
https://scholar.google.com/scholar?cluster=8665350708819483356&hl=en&as_sdt=0,5
| 2 | 2,022 |
A Broad Study of Pre-training for Domain Generalization and Adaptation
| 22 |
eccv
| 2 | 1 |
2023-06-17 00:59:51.709000
|
https://github.com/visionlearninggroup/benchmark_domain_transfer
| 11 |
A broad study of pre-training for domain generalization and adaptation
|
https://scholar.google.com/scholar?cluster=4743623741984149169&hl=en&as_sdt=0,5
| 2 | 2,022 |
Prior Knowledge Guided Unsupervised Domain Adaptation
| 6 |
eccv
| 1 | 0 |
2023-06-17 00:59:51.920000
|
https://github.com/tsun/kuda
| 12 |
Prior Knowledge Guided Unsupervised Domain Adaptation
|
https://scholar.google.com/scholar?cluster=16331707540385180374&hl=en&as_sdt=0,5
| 2 | 2,022 |
AcroFOD: An Adaptive Method for Cross-Domain Few-Shot Object Detection
| 6 |
eccv
| 4 | 0 |
2023-06-17 00:59:52.133000
|
https://github.com/hlings/acrofod
| 30 |
AcroFOD: An Adaptive Method for Cross-Domain Few-Shot Object Detection
|
https://scholar.google.com/scholar?cluster=8976863318013390692&hl=en&as_sdt=0,10
| 2 | 2,022 |
Visual Prompt Tuning
| 249 |
eccv
| 63 | 7 |
2023-06-17 00:59:52.346000
|
https://github.com/KMnP/vpt
| 561 |
Visual prompt tuning
|
https://scholar.google.com/scholar?cluster=14421942083121350206&hl=en&as_sdt=0,5
| 8 | 2,022 |
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