{"list":"other","total":59,"rows":[{"id":"1412.6980","title":"Adam: A Method for Stochastic Optimization","created":"2014-12-22","cited_by_count":37240},{"id":"1710.09412","title":"mixup: Beyond Empirical Risk Minimization","created":"2017-10-25","cited_by_count":5183},{"id":"1604.01685","title":"The Cityscapes Dataset for Semantic Urban Scene Understanding","created":"2016-04-06","cited_by_count":4444},{"id":"1606.00915","title":"DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs","created":"2016-06-02","cited_by_count":3241},{"id":"1905.04899","title":"CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features","created":"2019-05-13","cited_by_count":2884},{"id":"1503.03832","title":"FaceNet: A Unified Embedding for Face Recognition and Clustering","created":"2015-03-12","cited_by_count":2849},{"id":"1706.05587","title":"Rethinking Atrous Convolution for Semantic Image Segmentation","created":"2017-06-17","cited_by_count":2161},{"id":"1908.07919","title":"Deep High-Resolution Representation Learning for Visual Recognition","created":"2019-08-20","cited_by_count":1420},{"id":"1905.02249","title":"MixMatch: A Holistic Approach to Semi-Supervised Learning","created":"2019-05-06","cited_by_count":1391},{"id":"1911.04252","title":"Self-training with Noisy Student improves ImageNet classification","created":"2019-11-11","cited_by_count":1311},{"id":"1608.02192","title":"Playing for Data: Ground Truth from Computer Games","created":"2016-08-07","cited_by_count":818},{"id":"1802.03601","title":"Deep Visual Domain Adaptation: A Survey","created":"2018-02-10","cited_by_count":635},{"id":"1811.12833","title":"ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation","created":"2018-11-30","cited_by_count":623},{"id":"1802.10349","title":"Learning to Adapt Structured Output Space for Semantic Segmentation","created":"2018-02-28","cited_by_count":584},{"id":"2004.05498","title":"FDA: Fourier Domain Adaptation for Semantic Segmentation","created":"2020-04-11","cited_by_count":541},{"id":"1511.06452","title":"Deep Metric Learning via Lifted Structured Feature Embedding","created":"2015-11-19","cited_by_count":449},{"id":"1908.09822","title":"Confidence Regularized Self-Training","created":"2019-08-26","cited_by_count":419},{"id":"1904.06627","title":"Multi-Similarity Loss with General Pair Weighting for Deep Metric Learning","created":"2019-04-14","cited_by_count":368},{"id":"1812.05720","title":"Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem","created":"2018-12-13","cited_by_count":323},{"id":"1904.10620","title":"Bidirectional Learning for Domain Adaptation of Semantic Segmentation","created":"2019-04-24","cited_by_count":308},{"id":"1703.07464","title":"No Fuss Distance Metric Learning using Proxies","created":"2017-03-21","cited_by_count":226},{"id":"2007.08702","title":"DACS: Domain Adaptation via Cross-domain Mixed Sampling","created":"2020-07-17","cited_by_count":226},{"id":"2003.03773","title":"Rectifying Pseudo Label Learning via Uncertainty Estimation for Domain Adaptive Semantic Segmentation","created":"2020-03-08","cited_by_count":222},{"id":"1508.04306","title":"Deep clustering: Discriminative embeddings for segmentation and separation","created":"2015-08-18","cited_by_count":212},{"id":"2007.07936","title":"ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised Learning","created":"2020-07-15","cited_by_count":209},{"id":"2004.07703","title":"Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision","created":"2020-04-16","cited_by_count":198},{"id":"2003.13911","title":"Proxy Anchor Loss for Deep Metric Learning","created":"2020-03-31","cited_by_count":195},{"id":"2212.01322","title":"MIC: Masked Image Consistency for Context-Enhanced Domain Adaptation","created":"2022-12-02","cited_by_count":178},{"id":"2008.12197","title":"Instance Adaptive Self-Training for Unsupervised Domain Adaptation","created":"2020-08-27","cited_by_count":177},{"id":"2103.16372","title":"Source-Free Domain Adaptation for Semantic Segmentation","created":"2021-03-30","cited_by_count":168},{"id":"1909.05235","title":"SoftTriple Loss: Deep Metric Learning Without Triplet Sampling","created":"2019-09-11","cited_by_count":163},{"id":"2003.00867","title":"Learning Texture Invariant Representation for Domain Adaptation of Semantic Segmentation","created":"2020-03-02","cited_by_count":153},{"id":"2110.03374","title":"Model Adaptation: Historical Contrastive Learning for Unsupervised Domain Adaptation without Source Data","created":"2021-10-07","cited_by_count":152},{"id":"1910.13049","title":"Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation","created":"2019-10-29","cited_by_count":151},{"id":"2105.00097","title":"Self-supervised Augmentation Consistency for Adapting Semantic Segmentation","created":"2021-04-30","cited_by_count":149},{"id":"1909.13589","title":"Domain Adaptation for Semantic Segmentation with Maximum Squares Loss","created":"2019-09-30","cited_by_count":138},{"id":"1909.00589","title":"Self-Ensembling with GAN-based Data Augmentation for Domain Adaptation in Semantic Segmentation","created":"2019-09-02","cited_by_count":126},{"id":"2003.08040","title":"Differential Treatment for Stuff and Things: A Simple Unsupervised Domain Adaptation Method for Semantic Segmentation","created":"2020-03-18","cited_by_count":126},{"id":"2103.03571","title":"Cycle Self-Training for Domain Adaptation","created":"2021-03-05","cited_by_count":120},{"id":"1812.05040","title":"Learning Semantic Segmentation from Synthetic Data: A Geometrically Guided Input-Output Adaptation Approach","created":"2018-12-12","cited_by_count":119},{"id":"1704.08509","title":"No More Discrimination: Cross City Adaptation of Road Scene Segmenters","created":"2017-04-27","cited_by_count":111},{"id":"2001.03182","title":"CrDoCo: Pixel-level Domain Transfer with Cross-Domain Consistency","created":"2020-01-09","cited_by_count":107},{"id":"2004.01113","title":"ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis","created":"2020-04-02","cited_by_count":107},{"id":"1903.12212","title":"All about Structure: Adapting Structural Information across Domains for Boosting Semantic Segmentation","created":"2019-03-26","cited_by_count":104},{"id":"2005.10876","title":"Unsupervised Domain Adaptation in Semantic Segmentation: a Review","created":"2020-05-21","cited_by_count":88},{"id":"2206.02066","title":"PIDNet: A Real-time Semantic Segmentation Network Inspired by PID Controllers","created":"2022-06-04","cited_by_count":84},{"id":"2108.11249","title":"Generalize then Adapt: Source-Free Domain Adaptive Semantic Segmentation","created":"2021-08-25","cited_by_count":81},{"id":"1903.03238","title":"Ranked List Loss for Deep Metric Learning","created":"2019-03-08","cited_by_count":77},{"id":"1804.03131","title":"Blazingly Fast Video Object Segmentation with Pixel-Wise Metric Learning","created":"2018-04-09","cited_by_count":74},{"id":"1711.08995","title":"Unsupervised Domain Adaptation with Similarity Learning","created":"2017-11-24","cited_by_count":73},{"id":"1909.03402","title":"Squeeze-and-Attention Networks for Semantic Segmentation","created":"2019-09-08","cited_by_count":61},{"id":"1505.07922","title":"Cross-domain Image Retrieval with a Dual Attribute-aware Ranking Network","created":"2015-05-29","cited_by_count":53},{"id":"2005.03697","title":"Source-Relaxed Domain Adaptation for Image Segmentation","created":"2020-05-07","cited_by_count":52},{"id":"2103.05254","title":"MetaCorrection: Domain-aware Meta Loss Correction for Unsupervised Domain Adaptation in Semantic Segmentation","created":"2021-03-09","cited_by_count":43},{"id":"2007.14449","title":"Learning from Scale-Invariant Examples for Domain Adaptation in Semantic Segmentation","created":"2020-07-28","cited_by_count":41},{"id":"2009.12559","title":"Affinity Space Adaptation for Semantic Segmentation Across Domains","created":"2020-09-26","cited_by_count":31},{"id":"2110.06484","title":"Domain Adaptive Semantic Segmentation without Source Data","created":"2021-10-13","cited_by_count":30},{"id":"1909.13776","title":"MLSL: Multi-Level Self-Supervised Learning for Domain Adaptation with Spatially Independent and Semantically Consistent Labeling","created":"2019-09-30","cited_by_count":20},{"id":"1807.02552","title":"M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning","created":"2018-07-06","cited_by_count":8}],"next_cursor":null}