{"total":21,"rows":[{"id":"2404.09451","title":"Contrastive Mean-Shift Learning for Generalized Category Discovery","created":"2024-04-15","cited_by_count":39,"area":null},{"id":"2408.04961","title":"In Defense of Lazy Visual Grounding for Open-Vocabulary Semantic Segmentation","created":"2024-08-09","cited_by_count":38,"area":null},{"id":"2407.09842","title":"Eliminating Feature Ambiguity for Few-Shot Segmentation","created":"2024-07-13","cited_by_count":19,"area":null},{"id":"2310.18737","title":"Pre-training with Random Orthogonal Projection Image Modeling","created":"2023-10-28","cited_by_count":11,"area":null},{"id":"2402.04599","title":"Meet JEANIE: a Similarity Measure for 3D Skeleton Sequences via Temporal-Viewpoint Alignment","created":"2024-02-07","cited_by_count":10,"area":null},{"id":"2309.09319","title":"Active Learning for Semantic Segmentation with Multi-class Label Query","created":"2023-09-17","cited_by_count":9,"area":null},{"id":"2409.11316","title":"MSDNet: Multi-Scale Decoder for Few-Shot Semantic Segmentation via Transformer-Guided Prototyping","created":"2024-09-17","cited_by_count":5,"area":null},{"id":"2307.09321","title":"Exploiting Field Dependencies for Learning on Categorical Data","created":"2023-07-18","cited_by_count":2,"area":null},{"id":"2311.12065","title":"Few-Shot Classification & Segmentation Using Large Language Models Agent","created":"2023-11-19","cited_by_count":2,"area":null},{"id":"2505.16625","title":"Background Matters: A Cross-view Bidirectional Modeling Framework for Semi-supervised Medical Image Segmentation","created":"2025-05-22","cited_by_count":2,"area":null},{"id":"2510.17188","title":"HIDISC: A Hyperbolic Framework for Domain Generalization with Generalized Category Discovery","created":"2025-10-20","cited_by_count":2,"area":null},{"id":"2408.08250","title":"Computer Vision Model Compression Techniques for Embedded Systems: A Survey","created":"2024-08-15","cited_by_count":1,"area":null},{"id":"2505.12547","title":"ProMi: An Efficient Prototype-Mixture Baseline for Few-Shot Segmentation with Bounding-Box Annotations","created":"2025-05-18","cited_by_count":1,"area":null},{"id":"2603.13660","title":"Learning Generalizable 3D Medical Image Representations from Mask-Guided Self-Supervision","created":"2026-03-14","cited_by_count":1,"area":null},{"id":"2603.21287","title":"Focus on Background: Exploring SAM's Potential in Few-shot Medical Image Segmentation with Background-centric Prompting","created":"2026-03-22","cited_by_count":1,"area":null},{"id":"2311.11592","title":"Predicting urban tree cover from incomplete point labels and limited background information","created":"2023-11-20","cited_by_count":0,"area":null},{"id":"2405.19638","title":"Learning Robust Correlation with Foundation Model for Weakly-Supervised Few-Shot Segmentation","created":"2024-05-30","cited_by_count":0,"area":null},{"id":"2507.01711","title":"Component Adaptive Clustering for Generalized Category Discovery","created":"2025-07-02","cited_by_count":0,"area":null},{"id":"2507.23642","title":"Efficient Masked Attention Transformer for Few-Shot Classification and Segmentation","created":"2025-07-31","cited_by_count":0,"area":null},{"id":"2509.15272","title":"Which Direction to Choose? An Analysis on the Representation Power of Self-Supervised ViTs in Downstream Tasks","created":"2025-09-18","cited_by_count":0,"area":null},{"id":"2603.14240","title":"FOCUS: Bridging Fine-Grained Recognition and Open-World Discovery across Domains","created":"2026-03-15","cited_by_count":0,"area":null}],"next_cursor":null}