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MEMO: Test Time Robustness via Adaptation and Augmentation
| 63 |
neurips
| 4 | 1 |
2023-06-16 23:00:44.854000
|
https://github.com/zhangmarvin/memo
| 34 |
Memo: Test time robustness via adaptation and augmentation
|
https://scholar.google.com/scholar?cluster=1448618539109048791&hl=en&as_sdt=0,11
| 2 | 2,022 |
Asymptotically Unbiased Instance-wise Regularized Partial AUC Optimization: Theory and Algorithm
| 0 |
neurips
| 0 | 0 |
2023-06-16 23:00:45.065000
|
https://github.com/shaocr/pauci
| 4 |
Asymptotically Unbiased Instance-wise Regularized Partial AUC Optimization: Theory and Algorithm
|
https://scholar.google.com/scholar?cluster=11237720995546922276&hl=en&as_sdt=0,10
| 2 | 2,022 |
Error Correction Code Transformer
| 7 |
neurips
| 6 | 0 |
2023-06-16 23:00:45.281000
|
https://github.com/yonilc/ecct
| 13 |
Error correction code transformer
|
https://scholar.google.com/scholar?cluster=903759423999065870&hl=en&as_sdt=0,33
| 2 | 2,022 |
Capturing Graphs with Hypo-Elliptic Diffusions
| 0 |
neurips
| 0 | 0 |
2023-06-16 23:00:45.499000
|
https://github.com/tgcsaba/graph2tens
| 2 |
Capturing Graphs with Hypo-Elliptic Diffusions
|
https://scholar.google.com/scholar?cluster=15681689406304217341&hl=en&as_sdt=0,10
| 1 | 2,022 |
SIXO: Smoothing Inference with Twisted Objectives
| 0 |
neurips
| 0 | 0 |
2023-06-16 23:00:45.712000
|
https://github.com/lindermanlab/sixo
| 3 |
SIXO: Smoothing Inference with Twisted Objectives
|
https://scholar.google.com/scholar?cluster=12038259047812745507&hl=en&as_sdt=0,34
| 3 | 2,022 |
Exploring evolution-aware & -free protein language models as protein function predictors
| 2 |
neurips
| 8 | 3 |
2023-06-16 16:57:06.093000
|
https://github.com/elttaes/revisiting-plms
| 40 |
On pre-trained language models for antibody
|
https://scholar.google.com/scholar?cluster=3644203748348349044&hl=en&as_sdt=0,33
| 2 | 2,022 |
Breaking Bad: A Dataset for Geometric Fracture and Reassembly
| 4 |
neurips
| 8 | 0 |
2023-06-16 23:00:45.923000
|
https://github.com/wuziyi616/multi_part_assembly
| 39 |
Breaking Bad: A Dataset for Geometric Fracture and Reassembly
|
https://scholar.google.com/scholar?cluster=14499530288450300317&hl=en&as_sdt=0,5
| 2 | 2,022 |
Geoclidean: Few-Shot Generalization in Euclidean Geometry
| 2 |
neurips
| 0 | 0 |
2023-06-16 23:00:46.136000
|
https://github.com/joyhsu0504/geoclidean_framework
| 6 |
Geoclidean: Few-shot generalization in euclidean geometry
|
https://scholar.google.com/scholar?cluster=15302234923717650723&hl=en&as_sdt=0,5
| 2 | 2,022 |
Structural Kernel Search via Bayesian Optimization and Symbolical Optimal Transport
| 1 |
neurips
| 0 | 0 |
2023-06-16 23:00:46.349000
|
https://github.com/boschresearch/bosot
| 0 |
Structural Kernel Search via Bayesian Optimization and Symbolical Optimal Transport
|
https://scholar.google.com/scholar?cluster=5846774864854783055&hl=en&as_sdt=0,4
| 3 | 2,022 |
Robust Models are less Over-Confident
| 1 |
neurips
| 1 | 0 |
2023-06-16 23:00:46.561000
|
https://github.com/gejulia/robustness_confidences_evaluation
| 17 |
Robust Models are less Over-Confident
|
https://scholar.google.com/scholar?cluster=11840327885361702172&hl=en&as_sdt=0,33
| 3 | 2,022 |
ComMU: Dataset for Combinatorial Music Generation
| 0 |
neurips
| 24 | 0 |
2023-06-16 23:00:46.773000
|
https://github.com/POZAlabs/ComMU-code
| 118 |
ComMU: Dataset for Combinatorial Music Generation
|
https://scholar.google.com/scholar?cluster=17767260003172440235&hl=en&as_sdt=0,5
| 6 | 2,022 |
Consensus-Driven Propagation in Massive Unlabeled Data for Face Recognition
| 83 |
eccv
| 91 | 0 |
2023-06-16 23:55:11.795000
|
https://github.com/XiaohangZhan/cdp
| 444 |
Consensus-driven propagation in massive unlabeled data for face recognition
|
https://scholar.google.com/scholar?cluster=3229094614013455360&hl=en&as_sdt=0,43
| 22 | 2,018 |
Deep Cross-Modal Projection Learning for Image-Text Matching
| 280 |
eccv
| 20 | 12 |
2023-06-16 23:55:12.010000
|
https://github.com/YingZhangDUT/Cross-Modal-Projection-Learning
| 88 |
Deep cross-modal projection learning for image-text matching
|
https://scholar.google.com/scholar?cluster=17800185495041580477&hl=en&as_sdt=0,5
| 2 | 2,018 |
Multi-Class Model Fitting by Energy Minimization and Mode-Seeking
| 41 |
eccv
| 2 | 0 |
2023-06-16 23:55:12.222000
|
https://github.com/danini/multi-x
| 14 |
Multi-class model fitting by energy minimization and mode-seeking
|
https://scholar.google.com/scholar?cluster=9207771737491685637&hl=en&as_sdt=0,5
| 3 | 2,018 |
Depth Estimation via Affinity Learned with Convolutional Spatial Propagation Network
| 261 |
eccv
| 95 | 25 |
2023-06-16 23:55:12.434000
|
https://github.com/XinJCheng/CSPN
| 482 |
Depth estimation via affinity learned with convolutional spatial propagation network
|
https://scholar.google.com/scholar?cluster=15331233772685404808&hl=en&as_sdt=0,18
| 20 | 2,018 |
Fast Light Field Reconstruction With Deep Coarse-To-Fine Modeling of Spatial-Angular Clues
| 121 |
eccv
| 9 | 2 |
2023-06-16 23:55:12.645000
|
https://github.com/angularsr/LightFieldAngularSR
| 16 |
Fast light field reconstruction with deep coarse-to-fine modeling of spatial-angular clues
|
https://scholar.google.com/scholar?cluster=2431722100986178790&hl=en&as_sdt=0,5
| 2 | 2,018 |
Deep Expander Networks: Efficient Deep Networks from Graph Theory
| 68 |
eccv
| 12 | 0 |
2023-06-16 23:55:12.856000
|
https://github.com/DrImpossible/Deep-Expander-Networks
| 43 |
Deep expander networks: Efficient deep networks from graph theory
|
https://scholar.google.com/scholar?cluster=14046312150868626891&hl=en&as_sdt=0,5
| 4 | 2,018 |
Attend and Rectify: a gated attention mechanism for fine-grained recovery
| 45 |
eccv
| 10 | 2 |
2023-06-16 23:55:13.067000
|
https://github.com/prlz77/attend-and-rectify
| 52 |
Attend and rectify: a gated attention mechanism for fine-grained recovery
|
https://scholar.google.com/scholar?cluster=13738598675286043975&hl=en&as_sdt=0,34
| 4 | 2,018 |
PyramidBox: A Context-assisted Single Shot Face Detector
| 369 |
eccv
| 2,965 | 869 |
2023-06-16 23:55:13.279000
|
https://github.com/PaddlePaddle/models
| 6,794 |
Pyramidbox: A context-assisted single shot face detector
|
https://scholar.google.com/scholar?cluster=15584112941596045225&hl=en&as_sdt=0,10
| 275 | 2,018 |
Learning to Blend Photos
| 9 |
eccv
| 1 | 3 |
2023-06-16 23:55:13.490000
|
https://github.com/hfslyc/LearnToBlend
| 51 |
Learning to blend photos
|
https://scholar.google.com/scholar?cluster=3769330447198783594&hl=en&as_sdt=0,5
| 11 | 2,018 |
Parallel Feature Pyramid Network for Object Detection
| 265 |
eccv
| 0 | 1 |
2023-06-16 23:55:13.702000
|
https://github.com/chosj95/PFPNet.pytorch
| 7 |
Parallel feature pyramid network for object detection
|
https://scholar.google.com/scholar?cluster=3087633766276723421&hl=en&as_sdt=0,44
| 4 | 2,018 |
AMC: AutoML for Model Compression and Acceleration on Mobile Devices
| 1,290 |
eccv
| 101 | 18 |
2023-06-16 23:55:13.914000
|
https://github.com/mit-han-lab/amc
| 389 |
Amc: Automl for model compression and acceleration on mobile devices
|
https://scholar.google.com/scholar?cluster=2282234460810497997&hl=en&as_sdt=0,5
| 17 | 2,018 |
Diverse Conditional Image Generation by Stochastic Regression with Latent Drop-Out Codes
| 4 |
eccv
| 0 | 0 |
2023-06-16 23:55:14.126000
|
https://github.com/SSAW14/Image_Generation_with_Latent_Code
| 5 |
Diverse conditional image generation by stochastic regression with latent drop-out codes
|
https://scholar.google.com/scholar?cluster=12901521834315921854&hl=en&as_sdt=0,39
| 3 | 2,018 |
PS-FCN: A Flexible Learning Framework for Photometric Stereo
| 125 |
eccv
| 31 | 0 |
2023-06-16 23:55:14.336000
|
https://github.com/guanyingc/PS-FCN
| 81 |
PS-FCN: A flexible learning framework for photometric stereo
|
https://scholar.google.com/scholar?cluster=2638846704814041836&hl=en&as_sdt=0,36
| 6 | 2,018 |
Instance-level Human Parsing via Part Grouping Network
| 294 |
eccv
| 101 | 38 |
2023-06-16 23:55:14.547000
|
https://github.com/Engineering-Course/CIHP_PGN
| 381 |
Instance-level human parsing via part grouping network
|
https://scholar.google.com/scholar?cluster=9349119763164764615&hl=en&as_sdt=0,41
| 17 | 2,018 |
Constrained Optimization Based Low-Rank Approximation of Deep Neural Networks
| 62 |
eccv
| 1 | 0 |
2023-06-16 23:55:14.759000
|
https://github.com/chongli-uw/cobla
| 2 |
Constrained optimization based low-rank approximation of deep neural networks
|
https://scholar.google.com/scholar?cluster=16361848153367526892&hl=en&as_sdt=0,14
| 2 | 2,018 |
CTAP: Complementary Temporal Action Proposal Generation
| 183 |
eccv
| 11 | 6 |
2023-06-16 23:55:14.969000
|
https://github.com/jiyanggao/CTAP
| 42 |
Ctap: Complementary temporal action proposal generation
|
https://scholar.google.com/scholar?cluster=6089124584810492910&hl=en&as_sdt=0,3
| 5 | 2,018 |
Dist-GAN: An Improved GAN using Distance Constraints
| 92 |
eccv
| 21 | 5 |
2023-06-16 23:55:15.180000
|
https://github.com/tntrung/gan
| 66 |
Dist-gan: An improved gan using distance constraints
|
https://scholar.google.com/scholar?cluster=14413655732899864103&hl=en&as_sdt=0,10
| 5 | 2,018 |
Towards End-to-End License Plate Detection and Recognition: A Large Dataset and Baseline
| 235 |
eccv
| 559 | 84 |
2023-06-16 23:55:15.391000
|
https://github.com/detectRecog/CCPD
| 1,964 |
Towards end-to-end license plate detection and recognition: A large dataset and baseline
|
https://scholar.google.com/scholar?cluster=14804408137924957473&hl=en&as_sdt=0,5
| 63 | 2,018 |
Cross-Modal and Hierarchical Modeling of Video and Text
| 115 |
eccv
| 6 | 2 |
2023-06-16 23:55:15.648000
|
https://github.com/Sha-Lab/CMHSE
| 17 |
Cross-modal and hierarchical modeling of video and text
|
https://scholar.google.com/scholar?cluster=4253130459603491568&hl=en&as_sdt=0,5
| 5 | 2,018 |
StarMap for Category-Agnostic Keypoint and Viewpoint Estimation
| 70 |
eccv
| 18 | 5 |
2023-06-16 23:55:15.858000
|
https://github.com/xingyizhou/StarMap
| 101 |
Starmap for category-agnostic keypoint and viewpoint estimation
|
https://scholar.google.com/scholar?cluster=182684951534940435&hl=en&as_sdt=0,5
| 10 | 2,018 |
Improving DNN Robustness to Adversarial Attacks using Jacobian Regularization
| 176 |
eccv
| 0 | 1 |
2023-06-16 23:55:16.069000
|
https://github.com/danieljakubovitz/Jacobian_Regularization
| 3 |
Improving dnn robustness to adversarial attacks using jacobian regularization
|
https://scholar.google.com/scholar?cluster=15145149459046831045&hl=en&as_sdt=0,5
| 1 | 2,018 |
Folded Recurrent Neural Networks for Future Video Prediction
| 103 |
eccv
| 12 | 2 |
2023-06-16 23:55:16.280000
|
https://github.com/moliusimon/frnn
| 39 |
Folded recurrent neural networks for future video prediction
|
https://scholar.google.com/scholar?cluster=14311378408238305215&hl=en&as_sdt=0,5
| 2 | 2,018 |
Look Before You Leap: Bridging Model-Free and Model-Based Reinforcement Learning for Planned-Ahead Vision-and-Language Navigation
| 200 |
eccv
| 120 | 41 |
2023-06-16 23:55:16.491000
|
https://github.com/peteanderson80/Matterport3DSimulator
| 378 |
Look before you leap: Bridging model-free and model-based reinforcement learning for planned-ahead vision-and-language navigation
|
https://scholar.google.com/scholar?cluster=4362703551818063501&hl=en&as_sdt=0,28
| 19 | 2,018 |
Acquisition of Localization Confidence for Accurate Object Detection
| 841 |
eccv
| 151 | 20 |
2023-06-16 23:55:16.703000
|
https://github.com/vacancy/PreciseRoIPooling
| 761 |
Acquisition of localization confidence for accurate object detection
|
https://scholar.google.com/scholar?cluster=14154791864857863721&hl=en&as_sdt=0,31
| 24 | 2,018 |
Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network
| 691 |
eccv
| 940 | 164 |
2023-06-16 23:55:16.914000
|
https://github.com/YadiraF/PRNet
| 4,799 |
Joint 3d face reconstruction and dense alignment with position map regression network
|
https://scholar.google.com/scholar?cluster=2161439188175601394&hl=en&as_sdt=0,26
| 190 | 2,018 |
Multimodal Unsupervised Image-to-image Translation
| 2,289 |
eccv
| 484 | 61 |
2023-06-16 23:55:17.125000
|
https://github.com/nvlabs/MUNIT
| 2,565 |
Multimodal unsupervised image-to-image translation
|
https://scholar.google.com/scholar?cluster=13317525907573308290&hl=en&as_sdt=0,6
| 76 | 2,018 |
Diverse feature visualizations reveal invariances in early layers of deep neural networks
| 25 |
eccv
| 0 | 0 |
2023-06-16 23:55:17.336000
|
https://github.com/sacadena/diverse_feature_vis
| 5 |
Diverse feature visualizations reveal invariances in early layers of deep neural networks
|
https://scholar.google.com/scholar?cluster=5475890318105532537&hl=en&as_sdt=0,5
| 5 | 2,018 |
Learning Dynamic Memory Networks for Object Tracking
| 285 |
eccv
| 12 | 4 |
2023-06-16 23:55:17.547000
|
https://github.com/skyoung/MemTrack
| 81 |
Learning dynamic memory networks for object tracking
|
https://scholar.google.com/scholar?cluster=5536802084548288754&hl=en&as_sdt=0,36
| 9 | 2,018 |
Statistically-motivated Second-order Pooling
| 51 |
eccv
| 2 | 1 |
2023-06-16 23:55:17.758000
|
https://github.com/kcyu2014/smsop
| 32 |
Statistically-motivated second-order pooling
|
https://scholar.google.com/scholar?cluster=12417165649470483444&hl=en&as_sdt=0,39
| 5 | 2,018 |
Improving Generalization via Scalable Neighborhood Component Analysis
| 125 |
eccv
| 0 | 0 |
2023-06-16 23:55:17.969000
|
https://github.com/zhirongw/snca.pytorch
| 8 |
Improving generalization via scalable neighborhood component analysis
|
https://scholar.google.com/scholar?cluster=1930762472534444949&hl=en&as_sdt=0,5
| 2 | 2,018 |
Distractor-aware Siamese Networks for Visual Object Tracking
| 1,214 |
eccv
| 360 | 31 |
2023-06-16 23:55:18.181000
|
https://github.com/foolwood/DaSiamRPN
| 1,228 |
Distractor-aware siamese networks for visual object tracking
|
https://scholar.google.com/scholar?cluster=5659298886572595606&hl=en&as_sdt=0,46
| 56 | 2,018 |
Escaping from Collapsing Modes in a Constrained Space
| 16 |
eccv
| 1 | 0 |
2023-06-16 23:55:18.392000
|
https://github.com/chang810249/BEGAN-CS
| 12 |
Escaping from collapsing modes in a constrained space
|
https://scholar.google.com/scholar?cluster=8912424288441556924&hl=en&as_sdt=0,10
| 2 | 2,018 |
Discriminative Region Proposal Adversarial Networks for High-Quality Image-to-Image Translation
| 53 |
eccv
| 9 | 6 |
2023-06-16 23:55:18.615000
|
https://github.com/godisboy/DRPAN
| 51 |
Discriminative region proposal adversarial networks for high-quality image-to-image translation
|
https://scholar.google.com/scholar?cluster=3209031446584734295&hl=en&as_sdt=0,5
| 6 | 2,018 |
Learning Blind Video Temporal Consistency
| 252 |
eccv
| 62 | 14 |
2023-06-16 23:55:18.826000
|
https://github.com/phoenix104104/fast_blind_video_consistency
| 367 |
Learning blind video temporal consistency
|
https://scholar.google.com/scholar?cluster=7698730627265999813&hl=en&as_sdt=0,50
| 9 | 2,018 |
Graph Distillation for Action Detection with Privileged Modalities
| 100 |
eccv
| 18 | 3 |
2023-06-16 23:55:19.037000
|
https://github.com/google/graph_distillation
| 64 |
Graph distillation for action detection with privileged modalities
|
https://scholar.google.com/scholar?cluster=11357384495865637099&hl=en&as_sdt=0,5
| 6 | 2,018 |
Efficient Uncertainty Estimation for Semantic Segmentation in Videos
| 99 |
eccv
| 8 | 2 |
2023-06-16 23:55:19.249000
|
https://github.com/andyhahaha/Efficient-Uncertainty-Video-Segmentation
| 22 |
Efficient uncertainty estimation for semantic segmentation in videos
|
https://scholar.google.com/scholar?cluster=12752926199091689307&hl=en&as_sdt=0,5
| 4 | 2,018 |
Seeing Deeply and Bidirectionally: A Deep Learning Approach for Single Image Reflection Removal
| 131 |
eccv
| 12 | 5 |
2023-06-16 23:55:19.460000
|
https://github.com/yangj1e/bdn-refremv
| 46 |
Seeing deeply and bidirectionally: A deep learning approach for single image reflection removal
|
https://scholar.google.com/scholar?cluster=10372612231120248014&hl=en&as_sdt=0,5
| 7 | 2,018 |
Learning SO(3) Equivariant Representations with Spherical CNNs
| 424 |
eccv
| 48 | 6 |
2023-06-16 23:55:19.671000
|
https://github.com/daniilidis-group/spherical-cnn
| 275 |
Learning so (3) equivariant representations with spherical cnns
|
https://scholar.google.com/scholar?cluster=13360112200606529500&hl=en&as_sdt=0,5
| 14 | 2,018 |
T2Net: Synthetic-to-Realistic Translation for Solving Single-Image Depth Estimation Tasks
| 162 |
eccv
| 41 | 8 |
2023-06-16 23:55:19.882000
|
https://github.com/lyndonzheng/Synthetic2Realistic
| 177 |
T2net: Synthetic-to-realistic translation for solving single-image depth estimation tasks
|
https://scholar.google.com/scholar?cluster=2045753887928749430&hl=en&as_sdt=0,5
| 6 | 2,018 |
Partial Adversarial Domain Adaptation
| 384 |
eccv
| 41 | 1 |
2023-06-16 23:55:20.094000
|
https://github.com/thuml/PADA
| 90 |
Partial adversarial domain adaptation
|
https://scholar.google.com/scholar?cluster=5435435641375957692&hl=en&as_sdt=0,33
| 11 | 2,018 |
Diverse Image-to-Image Translation via Disentangled Representations
| 1,135 |
eccv
| 153 | 30 |
2023-06-16 23:55:20.305000
|
https://github.com/HsinYingLee/DRIT
| 810 |
Diverse image-to-image translation via disentangled representations
|
https://scholar.google.com/scholar?cluster=2272463241175511122&hl=en&as_sdt=0,20
| 15 | 2,018 |
BOP: Benchmark for 6D Object Pose Estimation
| 334 |
eccv
| 112 | 7 |
2023-06-16 23:55:20.515000
|
https://github.com/thodan/bop_toolkit
| 287 |
Bop: Benchmark for 6d object pose estimation
|
https://scholar.google.com/scholar?cluster=7913199704113527&hl=en&as_sdt=0,5
| 11 | 2,018 |
Generative Domain-Migration Hashing for Sketch-to-Image Retrieval
| 85 |
eccv
| 6 | 3 |
2023-06-16 23:55:20.726000
|
https://github.com/YCJGG/GDH
| 21 |
Generative domain-migration hashing for sketch-to-image retrieval
|
https://scholar.google.com/scholar?cluster=11613774012144257188&hl=en&as_sdt=0,5
| 2 | 2,018 |
FloorNet: A Unified Framework for Floorplan Reconstruction from 3D Scans
| 122 |
eccv
| 49 | 15 |
2023-06-16 23:55:20.936000
|
https://github.com/art-programmer/FloorNet
| 189 |
Floornet: A unified framework for floorplan reconstruction from 3d scans
|
https://scholar.google.com/scholar?cluster=6050985589125390059&hl=en&as_sdt=0,5
| 12 | 2,018 |
DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency
| 442 |
eccv
| 33 | 4 |
2023-06-16 23:55:21.147000
|
https://github.com/vt-vl-lab/DF-Net
| 209 |
Df-net: Unsupervised joint learning of depth and flow using cross-task consistency
|
https://scholar.google.com/scholar?cluster=14124367292083542005&hl=en&as_sdt=0,6
| 9 | 2,018 |
Hierarchical Bilinear Pooling for Fine-Grained Visual Recognition
| 278 |
eccv
| 23 | 7 |
2023-06-16 23:55:21.358000
|
https://github.com/ChaojianYu/Hierarchical-Bilinear-Pooling
| 102 |
Hierarchical bilinear pooling for fine-grained visual recognition
|
https://scholar.google.com/scholar?cluster=4033149798374032404&hl=en&as_sdt=0,5
| 1 | 2,018 |
Face De-Spoofing: Anti-Spoofing via Noise Modeling
| 265 |
eccv
| 42 | 15 |
2023-06-16 23:55:21.569000
|
https://github.com/yaojieliu/ECCV2018-FaceDeSpoofing
| 143 |
Face de-spoofing: Anti-spoofing via noise modeling
|
https://scholar.google.com/scholar?cluster=6923482401871998322&hl=en&as_sdt=0,23
| 8 | 2,018 |
Efficient Relative Attribute Learning using Graph Neural Networks
| 30 |
eccv
| 4 | 1 |
2023-06-16 23:55:21.780000
|
https://github.com/zihangm/RAL_GNN
| 20 |
Efficient relative attribute learning using graph neural networks
|
https://scholar.google.com/scholar?cluster=11106726889748018924&hl=en&as_sdt=0,5
| 0 | 2,018 |
Localization Recall Precision (LRP): A New Performance Metric for Object Detection
| 115 |
eccv
| 13 | 0 |
2023-06-16 23:55:21.992000
|
https://github.com/cancam/LRP
| 63 |
Localization recall precision (LRP): A new performance metric for object detection
|
https://scholar.google.com/scholar?cluster=18184659199813329105&hl=en&as_sdt=0,5
| 8 | 2,018 |
Image Super-Resolution Using Very Deep Residual Channel Attention Networks
| 3,523 |
eccv
| 319 | 76 |
2023-06-16 23:55:22.204000
|
https://github.com/yulunzhang/RCAN
| 1,245 |
Image super-resolution using very deep residual channel attention networks
|
https://scholar.google.com/scholar?cluster=3748973811121591896&hl=en&as_sdt=0,10
| 21 | 2,018 |
Extending Layered Models to 3D Motion
| 32 |
eccv
| 0 | 0 |
2023-06-16 23:55:22.414000
|
https://github.com/donglao/layers3Dmotion
| 2 |
Extending layered models to 3d motion
|
https://scholar.google.com/scholar?cluster=3699102061773173844&hl=en&as_sdt=0,25
| 3 | 2,018 |
License Plate Detection and Recognition in Unconstrained Scenarios
| 268 |
eccv
| 595 | 112 |
2023-06-16 23:55:22.641000
|
https://github.com/sergiomsilva/alpr-unconstrained
| 1,623 |
License plate detection and recognition in unconstrained scenarios
|
https://scholar.google.com/scholar?cluster=12853420144391201059&hl=en&as_sdt=0,5
| 87 | 2,018 |
ShapeStacks: Learning Vision-Based Physical Intuition for Generalised Object Stacking
| 85 |
eccv
| 10 | 8 |
2023-06-16 23:55:22.851000
|
https://github.com/ogroth/shapestacks
| 41 |
Shapestacks: Learning vision-based physical intuition for generalised object stacking
|
https://scholar.google.com/scholar?cluster=11796899814392889836&hl=en&as_sdt=0,5
| 5 | 2,018 |
SRDA: Generating Instance Segmentation Annotation via Scanning, Reasoning and Domain Adaptation
| 19 |
eccv
| 1 | 0 |
2023-06-16 23:55:23.064000
|
https://github.com/DirtyHarryLYL/SRDA-ECCV2018
| 7 |
Srda: Generating instance segmentation annotation via scanning, reasoning and domain adaptation
|
https://scholar.google.com/scholar?cluster=14701934472659497490&hl=en&as_sdt=0,5
| 2 | 2,018 |
On the Solvability of Viewing Graphs
| 10 |
eccv
| 0 | 0 |
2023-06-16 23:55:23.278000
|
https://github.com/mtrager/viewing-graphs
| 1 |
On the solvability of viewing graphs
|
https://scholar.google.com/scholar?cluster=11272659149049993124&hl=en&as_sdt=0,5
| 2 | 2,018 |
A Systematic DNN Weight Pruning Framework using Alternating Direction Method of Multipliers
| 390 |
eccv
| 33 | 6 |
2023-06-16 23:55:23.490000
|
https://github.com/KaiqiZhang/admm-pruning
| 95 |
A systematic dnn weight pruning framework using alternating direction method of multipliers
|
https://scholar.google.com/scholar?cluster=17353545770360369624&hl=en&as_sdt=0,5
| 8 | 2,018 |
Single Shot Scene Text Retrieval
| 42 |
eccv
| 30 | 1 |
2023-06-16 23:55:23.702000
|
https://github.com/lluisgomez/single-shot-str
| 66 |
Single shot scene text retrieval
|
https://scholar.google.com/scholar?cluster=18342223451780815542&hl=en&as_sdt=0,5
| 10 | 2,018 |
Deep Shape Matching
| 76 |
eccv
| 47 | 5 |
2023-06-16 23:55:23.922000
|
https://github.com/janesjanes/sketchy
| 157 |
Deep shape matching
|
https://scholar.google.com/scholar?cluster=8039392131029835381&hl=en&as_sdt=0,33
| 6 | 2,018 |
Learning to Navigate for Fine-grained Classification
| 462 |
eccv
| 119 | 38 |
2023-06-16 23:55:24.134000
|
https://github.com/yangze0930/NTS-Net
| 435 |
Learning to navigate for fine-grained classification
|
https://scholar.google.com/scholar?cluster=14152137546438136393&hl=en&as_sdt=0,5
| 11 | 2,018 |
Improving Shape Deformation in Unsupervised Image-to-Image Translation
| 80 |
eccv
| 22 | 17 |
2023-06-16 23:55:24.347000
|
https://github.com/brownvc/ganimorph
| 119 |
Improving shape deformation in unsupervised image-to-image translation
|
https://scholar.google.com/scholar?cluster=8740306489765068872&hl=en&as_sdt=0,5
| 17 | 2,018 |
LSQ++: Lower running time and higher recall in multi-codebook quantization
| 31 |
eccv
| 4 | 27 |
2023-06-16 23:55:24.565000
|
https://github.com/una-dinosauria/Rayuela.jl
| 57 |
LSQ++: Lower running time and higher recall in multi-codebook quantization
|
https://scholar.google.com/scholar?cluster=2638321853527220522&hl=en&as_sdt=0,11
| 5 | 2,018 |
Depth-aware CNN for RGB-D Segmentation
| 240 |
eccv
| 83 | 34 |
2023-06-16 23:55:24.802000
|
https://github.com/laughtervv/DepthAwareCNN
| 292 |
Depth-aware cnn for rgb-d segmentation
|
https://scholar.google.com/scholar?cluster=13093843379314761716&hl=en&as_sdt=0,23
| 14 | 2,018 |
Weakly- and Semi-Supervised Panoptic Segmentation
| 177 |
eccv
| 24 | 0 |
2023-06-16 23:55:25.039000
|
https://github.com/qizhuli/Weakly-Supervised-Panoptic-Segmentation
| 159 |
Weakly-and semi-supervised panoptic segmentation
|
https://scholar.google.com/scholar?cluster=7210150945066091860&hl=en&as_sdt=0,41
| 12 | 2,018 |
Learning Rigidity in Dynamic Scenes with a Moving Camera for 3D Motion Field Estimation
| 79 |
eccv
| 20 | 3 |
2023-06-16 23:55:25.251000
|
https://github.com/NVlabs/learningrigidity
| 143 |
Learning rigidity in dynamic scenes with a moving camera for 3d motion field estimation
|
https://scholar.google.com/scholar?cluster=827835377637646447&hl=en&as_sdt=0,10
| 17 | 2,018 |
Textual Explanations for Self-Driving Vehicles
| 214 |
eccv
| 14 | 9 |
2023-06-16 23:55:25.463000
|
https://github.com/JinkyuKimUCB/explainable-deep-driving
| 51 |
Textual explanations for self-driving vehicles
|
https://scholar.google.com/scholar?cluster=3588149335447094159&hl=en&as_sdt=0,5
| 4 | 2,018 |
Shuffle-Then-Assemble: Learning Object-Agnostic Visual Relationship Features
| 79 |
eccv
| 30 | 19 |
2023-06-16 23:55:25.674000
|
https://github.com/yangxuntu/vrd
| 90 |
Shuffle-then-assemble: Learning object-agnostic visual relationship features
|
https://scholar.google.com/scholar?cluster=11457586717303926687&hl=en&as_sdt=0,5
| 4 | 2,018 |
Revisiting the Inverted Indices for Billion-Scale Approximate Nearest Neighbors
| 67 |
eccv
| 21 | 2 |
2023-06-16 23:55:25.885000
|
https://github.com/dbaranchuk/ivf-hnsw
| 163 |
Revisiting the inverted indices for billion-scale approximate nearest neighbors
|
https://scholar.google.com/scholar?cluster=17143188662932206713&hl=en&as_sdt=0,33
| 6 | 2,018 |
Pyramid Dilated Deeper ConvLSTM for Video Salient Object Detection
| 441 |
eccv
| 27 | 7 |
2023-06-16 23:55:26.096000
|
https://github.com/shenjianbing/PDB-ConvLSTM
| 113 |
Pyramid dilated deeper convlstm for video salient object detection
|
https://scholar.google.com/scholar?cluster=4923326738440851048&hl=en&as_sdt=0,32
| 9 | 2,018 |
Beyond local reasoning for stereo confidence estimation with deep learning
| 59 |
eccv
| 5 | 1 |
2023-06-16 23:55:26.308000
|
https://github.com/fabiotosi92/LGC-Tensorflow
| 10 |
Beyond local reasoning for stereo confidence estimation with deep learning
|
https://scholar.google.com/scholar?cluster=15944809692028106974&hl=en&as_sdt=0,23
| 3 | 2,018 |
Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights
| 487 |
eccv
| 23 | 2 |
2023-06-16 23:55:26.518000
|
https://github.com/arunmallya/piggyback
| 172 |
Piggyback: Adapting a single network to multiple tasks by learning to mask weights
|
https://scholar.google.com/scholar?cluster=14326835779502008295&hl=en&as_sdt=0,5
| 4 | 2,018 |
PSANet: Point-wise Spatial Attention Network for Scene Parsing
| 918 |
eccv
| 37 | 1 |
2023-06-16 23:55:26.730000
|
https://github.com/hszhao/PSANet
| 216 |
Psanet: Point-wise spatial attention network for scene parsing
|
https://scholar.google.com/scholar?cluster=5612902286487550404&hl=en&as_sdt=0,5
| 12 | 2,018 |
SkipNet: Learning Dynamic Routing in Convolutional Networks
| 561 |
eccv
| 47 | 7 |
2023-06-16 23:55:26.941000
|
https://github.com/ucbdrive/skipnet
| 223 |
Skipnet: Learning dynamic routing in convolutional networks
|
https://scholar.google.com/scholar?cluster=16831193156348049998&hl=en&as_sdt=0,18
| 14 | 2,018 |
The Contextual Loss for Image Transformation with Non-Aligned Data
| 333 |
eccv
| 78 | 13 |
2023-06-16 23:55:27.151000
|
https://github.com/roimehrez/contextualLoss
| 472 |
The contextual loss for image transformation with non-aligned data
|
https://scholar.google.com/scholar?cluster=4201014753742149913&hl=en&as_sdt=0,19
| 19 | 2,018 |
Fully-Convolutional Point Networks for Large-Scale Point Clouds
| 180 |
eccv
| 23 | 3 |
2023-06-16 23:55:27.362000
|
https://github.com/drethage/fully-convolutional-point-network
| 86 |
Fully-convolutional point networks for large-scale point clouds
|
https://scholar.google.com/scholar?cluster=15796798606510706475&hl=en&as_sdt=0,30
| 13 | 2,018 |
Integral Human Pose Regression
| 725 |
eccv
| 75 | 10 |
2023-06-16 23:55:27.573000
|
https://github.com/JimmySuen/integral-human-pose
| 456 |
Integral human pose regression
|
https://scholar.google.com/scholar?cluster=13367121804975374310&hl=en&as_sdt=0,5
| 25 | 2,018 |
A Dataset and Architecture for Visual Reasoning with a Working Memory
| 51 |
eccv
| 13 | 0 |
2023-06-16 23:55:27.784000
|
https://github.com/google/cog
| 41 |
A dataset and architecture for visual reasoning with a working memory
|
https://scholar.google.com/scholar?cluster=7092743520972213867&hl=en&as_sdt=0,3
| 7 | 2,018 |
Affinity Derivation and Graph Merge for Instance Segmentation
| 103 |
eccv
| 8 | 3 |
2023-06-16 23:55:27.995000
|
https://github.com/xck36/GMIS
| 39 |
Affinity derivation and graph merge for instance segmentation
|
https://scholar.google.com/scholar?cluster=10478540241382688376&hl=en&as_sdt=0,11
| 4 | 2,018 |
Modality Distillation with Multiple Stream Networks for Action Recognition
| 154 |
eccv
| 3 | 3 |
2023-06-16 23:55:28.207000
|
https://github.com/ncgarcia/modality-distillation
| 21 |
Modality distillation with multiple stream networks for action recognition
|
https://scholar.google.com/scholar?cluster=11766651177768406473&hl=en&as_sdt=0,11
| 4 | 2,018 |
Unsupervised Domain Adaptation for 3D Keypoint Estimation via View Consistency
| 33 |
eccv
| 7 | 3 |
2023-06-16 23:55:28.418000
|
https://github.com/xingyizhou/3DKeypoints-DA
| 82 |
Unsupervised domain adaptation for 3d keypoint estimation via view consistency
|
https://scholar.google.com/scholar?cluster=10330474330891828727&hl=en&as_sdt=0,14
| 11 | 2,018 |
Group Normalization
| 3,074 |
eccv
| 20 | 1 |
2023-06-16 23:55:28.643000
|
https://github.com/ppwwyyxx/GroupNorm-reproduce
| 113 |
Group normalization
|
https://scholar.google.com/scholar?cluster=14814179610283147593&hl=en&as_sdt=0,5
| 6 | 2,018 |
Conditional Image-Text Embedding Networks
| 103 |
eccv
| 91 | 1 |
2023-06-16 23:55:28.855000
|
https://github.com/BryanPlummer/cite
| 38 |
Conditional image-text embedding networks
|
https://scholar.google.com/scholar?cluster=16144402408937710486&hl=en&as_sdt=0,44
| 2 | 2,018 |
Object Level Visual Reasoning in Videos
| 161 |
eccv
| 20 | 5 |
2023-06-16 23:55:29.066000
|
https://github.com/fabienbaradel/object_level_visual_reasoning
| 172 |
Object level visual reasoning in videos
|
https://scholar.google.com/scholar?cluster=17632579279713545301&hl=en&as_sdt=0,5
| 15 | 2,018 |
Deep Clustering for Unsupervised Learning of Visual Features
| 2,326 |
eccv
| 310 | 8 |
2023-06-16 23:55:29.277000
|
https://github.com/facebookresearch/deepcluster
| 1,549 |
Deep clustering for unsupervised learning of visual features
|
https://scholar.google.com/scholar?cluster=9776210521429980111&hl=en&as_sdt=0,10
| 33 | 2,018 |
Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models
| 364 |
eccv
| 21 | 1 |
2023-06-16 23:55:29.488000
|
https://github.com/huanzhang12/Adversarial_Survey
| 98 |
Is Robustness the Cost of Accuracy?--A Comprehensive Study on the Robustness of 18 Deep Image Classification Models
|
https://scholar.google.com/scholar?cluster=380810929013428531&hl=en&as_sdt=0,5
| 8 | 2,018 |
Single Image Water Hazard Detection using FCN with Reflection Attention Units
| 30 |
eccv
| 16 | 12 |
2023-06-16 23:55:29.700000
|
https://github.com/Cow911/SingleImageWaterHazardDetectionWithRAU
| 50 |
Single image water hazard detection using fcn with reflection attention units
|
https://scholar.google.com/scholar?cluster=7504719303538721682&hl=en&as_sdt=0,44
| 4 | 2,018 |
Predicting Gaze in Egocentric Video by Learning Task-dependent Attention Transition
| 103 |
eccv
| 18 | 1 |
2023-06-16 23:55:29.911000
|
https://github.com/hyf015/egocentric-gaze-prediction
| 55 |
Predicting gaze in egocentric video by learning task-dependent attention transition
|
https://scholar.google.com/scholar?cluster=1151610918319195215&hl=en&as_sdt=0,24
| 4 | 2,018 |
Joint Learning of Intrinsic Images and Semantic Segmentation
| 43 |
eccv
| 1 | 1 |
2023-06-16 23:55:30.123000
|
https://github.com/Morpheus3000/intrinseg
| 12 |
Joint learning of intrinsic images and semantic segmentation
|
https://scholar.google.com/scholar?cluster=76148957542870676&hl=en&as_sdt=0,11
| 2 | 2,018 |
Bidirectional Feature Pyramid Network with Recurrent Attention Residual Modules for Shadow Detection
| 183 |
eccv
| 26 | 13 |
2023-06-16 23:55:30.335000
|
https://github.com/zijundeng/BDRAR
| 112 |
Bidirectional feature pyramid network with recurrent attention residual modules for shadow detection
|
https://scholar.google.com/scholar?cluster=9596477260782472154&hl=en&as_sdt=0,5
| 7 | 2,018 |
Deep Regression Tracking with Shrinkage Loss
| 238 |
eccv
| 14 | 2 |
2023-06-16 23:55:30.546000
|
https://github.com/chaoma99/DSLT
| 58 |
Deep regression tracking with shrinkage loss
|
https://scholar.google.com/scholar?cluster=13852835873107246854&hl=en&as_sdt=0,14
| 9 | 2,018 |
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