{"total":100,"rows":[{"id":"2102.06191","title":"Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals","created":"2021-02-11","cited_by_count":190,"area":null},{"id":"2203.15224","title":"Panoptic NeRF: 3D-to-2D Label Transfer for Panoptic Urban Scene Segmentation","created":"2022-03-29","cited_by_count":152,"area":null},{"id":"2105.08965","title":"Railroad is not a Train: Saliency as Pseudo-pixel Supervision for Weakly Supervised Semantic Segmentation","created":"2021-05-19","cited_by_count":127,"area":null},{"id":"2103.14862","title":"TS-CAM: Token Semantic Coupled Attention Map for Weakly Supervised Object Localization","created":"2021-03-27","cited_by_count":123,"area":null},{"id":"2206.07045","title":"ReCo: Retrieve and Co-segment for Zero-shot Transfer","created":"2022-06-14","cited_by_count":117,"area":null},{"id":"2102.11436","title":"Model-Based Domain Generalization","created":"2021-02-23","cited_by_count":104,"area":null},{"id":"2104.06064","title":"Mixed supervision for surface-defect detection: from weakly to fully supervised learning","created":"2021-04-13","cited_by_count":101,"area":null},{"id":"2104.10834","title":"DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation","created":"2021-04-22","cited_by_count":80,"area":null},{"id":"2107.11787","title":"Leveraging Auxiliary Tasks with Affinity Learning for Weakly Supervised Semantic Segmentation","created":"2021-07-25","cited_by_count":77,"area":null},{"id":"2203.02668","title":"Cross Language Image Matching for Weakly Supervised Semantic Segmentation","created":"2022-03-05","cited_by_count":72,"area":null},{"id":"2103.01795","title":"Context Decoupling Augmentation for Weakly Supervised Semantic Segmentation","created":"2021-03-02","cited_by_count":69,"area":null},{"id":"2203.08537","title":"Scribble-Supervised LiDAR Semantic Segmentation","created":"2022-03-16","cited_by_count":69,"area":null},{"id":"2203.01475","title":"CycleMix: A Holistic Strategy for Medical Image Segmentation from Scribble Supervision","created":"2022-03-03","cited_by_count":64,"area":null},{"id":"2108.12995","title":"Pseudo-mask Matters in Weakly-supervised Semantic Segmentation","created":"2021-08-30","cited_by_count":48,"area":null},{"id":"2106.02740","title":"ZeroWaste Dataset: Towards Deformable Object Segmentation in Cluttered Scenes","created":"2021-06-04","cited_by_count":47,"area":null},{"id":"2103.04523","title":"Unveiling the Potential of Structure Preserving for Weakly Supervised Object Localization","created":"2021-03-08","cited_by_count":46,"area":null},{"id":"2105.00957","title":"Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning","created":"2021-05-03","cited_by_count":43,"area":null},{"id":"2110.15767","title":"Adversarial Robustness with Semi-Infinite Constrained Learning","created":"2021-10-29","cited_by_count":39,"area":null},{"id":"2112.01882","title":"Incremental Learning in Semantic Segmentation from Image Labels","created":"2021-12-03","cited_by_count":39,"area":null},{"id":"2203.16045","title":"Threshold Matters in WSSS: Manipulating the Activation for the Robust and Accurate Segmentation Model Against Thresholds","created":"2022-03-30","cited_by_count":37,"area":null},{"id":"2105.06461","title":"3D Spatial Recognition without Spatially Labeled 3D","created":"2021-05-13","cited_by_count":31,"area":null},{"id":"2410.10807","title":"HardNet: Hard-Constrained Neural Networks with Universal Approximation Guarantees","created":"2024-10-14","cited_by_count":31,"area":null},{"id":"2112.07431","title":"Uncertainty Estimation via Response Scaling for Pseudo-mask Noise Mitigation in Weakly-supervised Semantic Segmentation","created":"2021-12-14","cited_by_count":29,"area":null},{"id":"2302.06378","title":"Semantic Image Segmentation: Two Decades of Research","created":"2023-02-13","cited_by_count":27,"area":null},{"id":"2109.07069","title":"F-CAM: Full Resolution Class Activation Maps via Guided Parametric Upscaling","created":"2021-09-15","cited_by_count":26,"area":null},{"id":"2110.15497","title":"Unsupervised Foreground Extraction via Deep Region Competition","created":"2021-10-29","cited_by_count":26,"area":"moe"},{"id":"2112.03185","title":"Semantic Segmentation In-the-Wild Without Seeing Any Segmentation Examples","created":"2021-12-06","cited_by_count":24,"area":null},{"id":"2109.14778","title":"CALDA: Improving Multi-Source Time Series Domain Adaptation with Contrastive Adversarial Learning","created":"2021-09-30","cited_by_count":23,"area":null},{"id":"2301.02830","title":"Image Data Augmentation Approaches: A Comprehensive Survey and Future directions","created":"2023-01-07","cited_by_count":23,"area":null},{"id":"2108.01344","title":"Adaptive Affinity Loss and Erroneous Pseudo-Label Refinement for Weakly Supervised Semantic Segmentation","created":"2021-08-03","cited_by_count":22,"area":null},{"id":"2210.14142","title":"From colouring-in to pointillism: revisiting semantic segmentation supervision","created":"2022-10-25","cited_by_count":22,"area":null},{"id":"2210.13950","title":"Pointly-Supervised Panoptic Segmentation","created":"2022-10-25","cited_by_count":21,"area":null},{"id":"2104.02967","title":"ACM-Net: Action Context Modeling Network for Weakly-Supervised Temporal Action Localization","created":"2021-04-07","cited_by_count":19,"area":null},{"id":"2203.01671","title":"Constrained unsupervised anomaly segmentation","created":"2022-03-03","cited_by_count":19,"area":null},{"id":"2204.11144","title":"Competitive Physics Informed Networks","created":"2022-04-23","cited_by_count":19,"area":null},{"id":"2310.13026","title":"Weakly-Supervised Semantic Segmentation with Image-Level Labels: from Traditional Models to Foundation Models","created":"2023-10-19","cited_by_count":19,"area":null},{"id":"2103.04854","title":"Injecting Knowledge in Data-driven Vehicle Trajectory Predictors","created":"2021-03-08","cited_by_count":18,"area":null},{"id":"2104.02488","title":"Weakly supervised segmentation with cross-modality equivariant constraints","created":"2021-04-06","cited_by_count":18,"area":null},{"id":"2108.07413","title":"Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised Segmentation","created":"2021-08-17","cited_by_count":13,"area":null},{"id":"2202.10337","title":"Integration of knowledge and data in machine learning","created":"2022-02-15","cited_by_count":13,"area":null},{"id":"2208.14542","title":"TCAM: Temporal Class Activation Maps for Object Localization in Weakly-Labeled Unconstrained Videos","created":"2022-08-30","cited_by_count":12,"area":null},{"id":"2409.01030","title":"Learning to Discover Forgery Cues for Face Forgery Detection","created":"2024-09-02","cited_by_count":11,"area":null},{"id":"2309.10815","title":"PanopticNeRF-360: Panoramic 3D-to-2D Label Transfer in Urban Scenes","created":"2023-09-19","cited_by_count":10,"area":null},{"id":"2302.02125","title":"Weakly-Supervised 3D Medical Image Segmentation using Geometric Prior and Contrastive Similarity","created":"2023-02-04","cited_by_count":9,"area":null},{"id":"2201.02445","title":"Negative Evidence Matters in Interpretable Histology Image Classification","created":"2022-01-07","cited_by_count":8,"area":null},{"id":"2308.11239","title":"LOCATE: Self-supervised Object Discovery via Flow-guided Graph-cut and Bootstrapped Self-training","created":"2023-08-22","cited_by_count":8,"area":null},{"id":"2410.11061","title":"Learning to Optimize for Mixed-Integer Non-linear Programming with Feasibility Guarantees","created":"2024-10-14","cited_by_count":8,"area":null},{"id":"2205.04227","title":"Mixed-UNet: Refined Class Activation Mapping for Weakly-Supervised Semantic Segmentation with Multi-scale Inference","created":"2022-05-06","cited_by_count":7,"area":null},{"id":"2303.09044","title":"CoLo-CAM: Class Activation Mapping for Object Co-Localization in Weakly-Labeled Unconstrained Videos","created":"2023-03-16","cited_by_count":7,"area":null},{"id":"2310.10533","title":"Label-efficient Segmentation via Affinity Propagation","created":"2023-10-16","cited_by_count":7,"area":null},{"id":"2109.13423","title":"Weakly Supervised Keypoint Discovery","created":"2021-09-28","cited_by_count":5,"area":null},{"id":"2104.07216","title":"Learning structure-aware semantic segmentation with image-level supervision","created":"2021-04-15","cited_by_count":4,"area":null},{"id":"2109.00482","title":"Looking at the whole picture: constrained unsupervised anomaly segmentation","created":"2021-09-01","cited_by_count":4,"area":null},{"id":"2111.10785","title":"Differentiable Projection for Constrained Deep Learning","created":"2021-11-21","cited_by_count":4,"area":null},{"id":"2206.05394","title":"Applications of Deep Learning in Fish Habitat Monitoring: A Tutorial and Survey","created":"2022-06-11","cited_by_count":4,"area":null},{"id":"2406.10855","title":"ALPS: An Auto-Labeling and Pre-training Scheme for Remote Sensing Segmentation With Segment Anything Model","created":"2024-06-16","cited_by_count":4,"area":null},{"id":"2407.10131","title":"WPS-SAM: Towards Weakly-Supervised Part Segmentation with Foundation Models","created":"2024-07-14","cited_by_count":4,"area":null},{"id":"2203.12459","title":"Importance Sampling CAMs for Weakly-Supervised Segmentation","created":"2022-03-23","cited_by_count":3,"area":null},{"id":"2307.00097","title":"Prompting classes: Exploring the Power of Prompt Class Learning in Weakly Supervised Semantic Segmentation","created":"2023-06-30","cited_by_count":3,"area":null},{"id":"2307.04392","title":"FODVid: Flow-guided Object Discovery in Videos","created":"2023-07-10","cited_by_count":3,"area":null},{"id":"2308.11376","title":"Boundary-RL: Reinforcement Learning for Weakly-Supervised Prostate Segmentation in TRUS Images","created":"2023-08-22","cited_by_count":3,"area":null},{"id":"2403.01156","title":"Auxiliary Tasks Enhanced Dual-affinity Learning for Weakly Supervised Semantic Segmentation","created":"2024-03-02","cited_by_count":3,"area":null},{"id":"2405.06288","title":"PCLMix: Weakly Supervised Medical Image Segmentation via Pixel-Level Contrastive Learning and Dynamic Mix Augmentation","created":"2024-05-10","cited_by_count":3,"area":null},{"id":"2103.11062","title":"Leveraging Unlabeled Data for Entity-Relation Extraction through Probabilistic Constraint Satisfaction","created":"2021-03-20","cited_by_count":2,"area":null},{"id":"2104.13082","title":"Weakly Supervised Volumetric Segmentation via Self-taught Shape Denoising Model","created":"2021-04-27","cited_by_count":2,"area":null},{"id":"2206.09148","title":"Deep Compatible Learning for Partially-Supervised Medical Image Segmentation","created":"2022-06-18","cited_by_count":2,"area":null},{"id":"2208.00974","title":"Information Gain Sampling for Active Learning in Medical Image Classification","created":"2022-08-01","cited_by_count":2,"area":null},{"id":"2211.12455","title":"ISIM: Iterative Self-Improved Model for Weakly Supervised Segmentation","created":"2022-11-22","cited_by_count":2,"area":null},{"id":"2301.07634","title":"Training Semantic Segmentation on Heterogeneous Datasets","created":"2023-01-18","cited_by_count":2,"area":null},{"id":"2301.12967","title":"Hierarchical learning, forecasting coherent spatio-temporal individual and aggregated building loads","created":"2023-01-30","cited_by_count":2,"area":null},{"id":"2507.02743","title":"Prompt learning with bounding box constraints for medical image segmentation","created":"2025-07-03","cited_by_count":2,"area":null},{"id":"2508.01250","title":"DisFaceRep: Representation Disentanglement for Co-occurring Facial Components in Weakly Supervised Face Parsing","created":"2025-08-02","cited_by_count":2,"area":null},{"id":"2104.01948","title":"Robust Trust Region for Weakly Supervised Segmentation","created":"2021-04-05","cited_by_count":1,"area":null},{"id":"2302.04729","title":"Constrained Empirical Risk Minimization: Theory and Practice","created":"2023-02-09","cited_by_count":1,"area":null},{"id":"2303.07853","title":"ReFit: A Framework for Refinement of Weakly Supervised Semantic Segmentation using Object Border Fitting for Medical Images","created":"2023-03-14","cited_by_count":1,"area":null},{"id":"2304.02621","title":"High-fidelity Pseudo-labels for Boosting Weakly-Supervised Segmentation","created":"2023-04-05","cited_by_count":1,"area":null},{"id":"2305.15608","title":"Semantic Segmentation by Semantic Proportions","created":"2023-05-24","cited_by_count":1,"area":null},{"id":"2307.11808","title":"Automatic Data Augmentation Learning using Bilevel Optimization for Histopathological Images","created":"2023-07-21","cited_by_count":1,"area":null},{"id":"2402.02474","title":"Deep Spectral Improvement for Unsupervised Image Instance Segmentation","created":"2024-02-04","cited_by_count":1,"area":null},{"id":"2403.18871","title":"Clinical Domain Knowledge-Derived Template Improves Post Hoc AI Explanations in Pneumothorax Classification","created":"2024-03-26","cited_by_count":1,"area":null},{"id":"2408.09411","title":"Weakly Supervised Lymph Nodes Segmentation Based on Partial Instance Annotations with Pre-trained Dual-branch Network and Pseudo Label Learning","created":"2024-08-18","cited_by_count":1,"area":null},{"id":"2409.17941","title":"Perturb, Attend, Detect and Localize (PADL): Robust Proactive Image Defense","created":"2024-09-26","cited_by_count":1,"area":null},{"id":"2501.16022","title":"SketchYourSeg: Mask-Free Subjective Image Segmentation via Freehand Sketches","created":"2025-01-27","cited_by_count":1,"area":null},{"id":"2501.16322","title":"Implicit Bias in Matrix Factorization and its Explicit Realization in a New Architecture","created":"2025-01-27","cited_by_count":1,"area":null},{"id":"2509.12496","title":"Localized Region Guidance for Class Activation Mapping in WSSS","created":"2025-09-15","cited_by_count":1,"area":null},{"id":"2107.05532","title":"Context-aware virtual adversarial training for anatomically-plausible segmentation","created":"2021-07-12","cited_by_count":0,"area":null},{"id":"2110.02651","title":"Weak Novel Categories without Tears: A Survey on Weak-Shot Learning","created":"2021-10-06","cited_by_count":0,"area":null},{"id":"2111.08401","title":"Weakly-supervised fire segmentation by visualizing intermediate CNN layers","created":"2021-11-16","cited_by_count":0,"area":null},{"id":"2203.10582","title":"Neuro-physical dynamic load modeling using differentiable parametric optimization","created":"2022-03-20","cited_by_count":0,"area":null},{"id":"2302.10895","title":"CQnet: convex-geometric interpretation and constraining neural-network trajectories","created":"2023-02-09","cited_by_count":0,"area":null},{"id":"2310.00307","title":"Dual-Augmented Transformer Network for Weakly Supervised Semantic Segmentation","created":"2023-09-30","cited_by_count":0,"area":null},{"id":"2401.06010","title":"Attention to detail: inter-resolution knowledge distillation","created":"2024-01-11","cited_by_count":0,"area":"distill"},{"id":"2409.01472","title":"Semantic Segmentation from Image Labels by Reconstruction from Structured Decomposition","created":"2024-09-02","cited_by_count":0,"area":null},{"id":"2409.04819","title":"Top-GAP: Integrating Size Priors in CNNs for more Interpretability, Robustness, and Bias Mitigation","created":"2024-09-07","cited_by_count":0,"area":null},{"id":"2503.06954","title":"Approximate Size Targets Are Sufficient for Accurate Semantic Segmentation","created":"2025-03-10","cited_by_count":0,"area":null},{"id":"2511.19765","title":"Lightweight Transformer Framework for Weakly Supervised Semantic Segmentation","created":"2025-11-24","cited_by_count":0,"area":null},{"id":"2604.11170","title":"Do Instance Priors Help Weakly Supervised Semantic Segmentation?","created":"2026-04-13","cited_by_count":0,"area":null},{"id":"2606.14555","title":"Rethinking Global Average Pooling: Your Classifier Is Secretly a Multi-Instance Learner","created":"2026-06-12","cited_by_count":0,"area":null},{"id":"2607.19669","title":"A Unified Variational Framework for Deep Weakly Supervised Image Segmentation","created":"2026-07-22","cited_by_count":0,"area":null},{"id":"2607.23751","title":"Soft-Constrained Optimization of Latent Space in Variational Autoencoders","created":"2026-07-26","cited_by_count":0,"area":null}],"next_cursor":null}