{"total":82,"rows":[{"id":"2306.05705","title":"On the Challenges and Perspectives of Foundation Models for Medical Image Analysis","created":"2023-06-09","cited_by_count":135,"area":null},{"id":"2304.05750","title":"Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applications","created":"2023-04-12","cited_by_count":121,"area":null},{"id":"2307.13721","title":"Foundational Models Defining a New Era in Vision: A Survey and Outlook","created":"2023-07-25","cited_by_count":110,"area":null},{"id":"2307.07494","title":"TALL: Thumbnail Layout for Deepfake Video Detection","created":"2023-07-14","cited_by_count":100,"area":null},{"id":"2504.03600","title":"MedSAM2: Segment Anything in 3D Medical Images and Videos","created":"2025-04-04","cited_by_count":96,"area":null},{"id":"2306.16741","title":"Foundation Model for Endoscopy Video Analysis via Large-scale Self-supervised Pre-train","created":"2023-06-29","cited_by_count":75,"area":null},{"id":"2306.06370","title":"AutoSAM: Adapting SAM to Medical Images by Overloading the Prompt Encoder","created":"2023-06-10","cited_by_count":70,"area":null},{"id":"2205.12853","title":"Deep Gradient Learning for Efficient Camouflaged Object Detection","created":"2022-05-25","cited_by_count":65,"area":null},{"id":"2309.05573","title":"UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebase","created":"2023-09-11","cited_by_count":57,"area":null},{"id":"2310.20208","title":"ZoomNeXt: A Unified Collaborative Pyramid Network for Camouflaged Object Detection","created":"2023-10-31","cited_by_count":48,"area":null},{"id":"2304.11234","title":"Advances in Deep Concealed Scene Understanding","created":"2023-04-21","cited_by_count":47,"area":null},{"id":"2408.03322","title":"Segment Anything in Medical Images and Videos: Benchmark and Deployment","created":"2024-08-06","cited_by_count":42,"area":null},{"id":"2207.13362","title":"Camouflaged Object Detection via Context-aware Cross-level Fusion","created":"2022-07-27","cited_by_count":32,"area":null},{"id":"2406.07471","title":"OphNet: A Large-Scale Video Benchmark for Ophthalmic Surgical Workflow Understanding","created":"2024-06-11","cited_by_count":32,"area":null},{"id":"2206.09309","title":"TBraTS: Trusted Brain Tumor Segmentation","created":"2022-06-19","cited_by_count":30,"area":null},{"id":"2305.17932","title":"CamoDiffusion: Camouflaged Object Detection via Conditional Diffusion Models","created":"2023-05-29","cited_by_count":21,"area":"diffusion"},{"id":"2307.10782","title":"See More and Know More: Zero-shot Point Cloud Segmentation via Multi-modal Visual Data","created":"2023-07-20","cited_by_count":21,"area":null},{"id":"2307.10912","title":"WeakPolyp: You Only Look Bounding Box for Polyp Segmentation","created":"2023-07-20","cited_by_count":21,"area":null},{"id":"2406.13532","title":"SALI: Short-term Alignment and Long-term Interaction Network for Colonoscopy Video Polyp Segmentation","created":"2024-06-19","cited_by_count":19,"area":null},{"id":"2409.19684","title":"MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generation","created":"2024-09-29","cited_by_count":17,"area":"mllm"},{"id":"2310.01861","title":"Shifting More Attention to Breast Lesion Segmentation in Ultrasound Videos","created":"2023-10-03","cited_by_count":16,"area":null},{"id":"2306.00451","title":"S$^2$ME: Spatial-Spectral Mutual Teaching and Ensemble Learning for Scribble-supervised Polyp Segmentation","created":"2023-06-01","cited_by_count":15,"area":null},{"id":"2410.17241","title":"Frontiers in Intelligent Colonoscopy","created":"2024-10-22","cited_by_count":14,"area":null},{"id":"2311.18373","title":"A Survey on Deep Learning for Polyp Segmentation: Techniques, Challenges and Future Trends","created":"2023-11-30","cited_by_count":12,"area":null},{"id":"2403.01968","title":"Explicit Motion Handling and Interactive Prompting for Video Camouflaged Object Detection","created":"2024-03-04","cited_by_count":11,"area":null},{"id":"2502.19090","title":"EndoMamba: An Efficient Foundation Model for Endoscopic Videos via Hierarchical Pre-training","created":"2025-02-26","cited_by_count":11,"area":"ssm"},{"id":"2307.15016","title":"How Good is Google Bard's Visual Understanding? An Empirical Study on Open Challenges","created":"2023-07-27","cited_by_count":9,"area":null},{"id":"2310.15098","title":"Acquiring Weak Annotations for Tumor Localization in Temporal and Volumetric Data","created":"2023-10-23","cited_by_count":9,"area":null},{"id":"2311.17122","title":"Large Model Based Referring Camouflaged Object Detection","created":"2023-11-28","cited_by_count":8,"area":null},{"id":"2503.19730","title":"CamSAM2: Segment Anything Accurately in Camouflaged Videos","created":"2025-03-25","cited_by_count":7,"area":null},{"id":"2509.06467","title":"Does DINOv3 Set a New Medical Vision Standard? Benchmarking 2D and 3D Classification, Segmentation, and Registration","created":"2025-09-08","cited_by_count":7,"area":null},{"id":"2409.07238","title":"Diff-VPS: Video Polyp Segmentation via a Multi-task Diffusion Network with Adversarial Temporal Reasoning","created":"2024-09-11","cited_by_count":6,"area":"diffusion"},{"id":"2409.09484","title":"Self-Prompting Polyp Segmentation in Colonoscopy using Hybrid Yolo-SAM 2 Model","created":"2024-09-14","cited_by_count":6,"area":null},{"id":"2312.08866","title":"MCANet: Medical Image Segmentation with Multi-Scale Cross-Axis Attention","created":"2023-12-14","cited_by_count":5,"area":null},{"id":"2401.11734","title":"Colorectal Polyp Segmentation in the Deep Learning Era: A Comprehensive Survey","created":"2024-01-22","cited_by_count":5,"area":null},{"id":"2603.17840","title":"Video Understanding: From Geometry and Semantics to Unified Models","created":"2026-03-18","cited_by_count":5,"area":null},{"id":"2306.07792","title":"Rethinking Polyp Segmentation from an Out-of-Distribution Perspective","created":"2023-06-13","cited_by_count":4,"area":null},{"id":"2401.04961","title":"ECC-PolypDet: Enhanced CenterNet with Contrastive Learning for Automatic Polyp Detection","created":"2024-01-10","cited_by_count":3,"area":null},{"id":"2405.12784","title":"Generalize Polyp Segmentation via Inpainting across Diverse Backgrounds and Pseudo-Mask Refinement","created":"2024-05-21","cited_by_count":3,"area":null},{"id":"2502.16841","title":"Fair Foundation Models for Medical Image Analysis: Challenges and Perspectives","created":"2025-02-24","cited_by_count":3,"area":null},{"id":"2503.22174","title":"Synergistic Bleeding Region and Point Detection in Laparoscopic Surgical Videos","created":"2025-03-28","cited_by_count":3,"area":null},{"id":"2506.00406","title":"iDPA: Instance Decoupled Prompt Attention for Incremental Medical Object Detection","created":"2025-05-31","cited_by_count":3,"area":null},{"id":"2407.05703","title":"HilbertMamba: Local-Global Reciprocal Network for Uterine Fibroid Segmentation in Ultrasound Videos","created":"2024-07-08","cited_by_count":2,"area":null},{"id":"2507.22792","title":"Segment Anything for Video: A Comprehensive Review of Video Object Segmentation and Tracking from Past to Future","created":"2025-07-30","cited_by_count":2,"area":null},{"id":"2512.17080","title":"Interpretable Similarity of Synthetic Image Utility","created":"2025-12-18","cited_by_count":2,"area":null},{"id":"2602.22821","title":"CMSA-Net: Causal Multi-scale Aggregation with Adaptive Multi-source Reference for Video Polyp Segmentation","created":"2026-02-26","cited_by_count":2,"area":null},{"id":"2602.23203","title":"ColoDiff: Integrating Dynamic Consistency With Content Awareness for Colonoscopy Video Generation","created":"2026-02-26","cited_by_count":2,"area":null},{"id":"2402.11585","title":"PolypNextLSTM: A lightweight and fast polyp video segmentation network using ConvNext and ConvLSTM","created":"2024-02-18","cited_by_count":1,"area":null},{"id":"2403.11699","title":"A Spatial-Temporal Progressive Fusion Network for Breast Lesion Segmentation in Ultrasound Videos","created":"2024-03-18","cited_by_count":1,"area":null},{"id":"2406.10200","title":"SSTFB: Leveraging self-supervised pretext learning and temporal self-attention with feature branching for real-time video polyp segmentation","created":"2024-06-14","cited_by_count":1,"area":null},{"id":"2412.16503","title":"First-frame Supervised Video Polyp Segmentation via Propagative and Semantic Dual-teacher Network","created":"2024-12-21","cited_by_count":1,"area":null},{"id":"2502.10294","title":"QMaxViT-Unet+: A Query-Based MaxViT-Unet with Edge Enhancement for Scribble-Supervised Segmentation of Medical Images","created":"2025-02-14","cited_by_count":1,"area":null},{"id":"2504.00375","title":"CamoSAM2: SAM2-oriented Prompt Auto-Refinement for Video Camouflaged Object Detection","created":"2025-04-01","cited_by_count":1,"area":null},{"id":"2507.20582","title":"M-Net: MRI Brain Tumor Sequential Segmentation Network via Mesh-Cast","created":"2025-07-28","cited_by_count":1,"area":null},{"id":"2507.22530","title":"HRVVS: A High-resolution Video Vasculature Segmentation Network via Hierarchical Autoregressive Residual Priors","created":"2025-07-30","cited_by_count":1,"area":null},{"id":"2508.01152","title":"LawDIS: Language-Window-based Controllable Dichotomous Image Segmentation","created":"2025-08-02","cited_by_count":1,"area":null},{"id":"2508.07585","title":"GAPNet: A Lightweight Framework for Image and Video Salient Object Detection via Granularity-Aware Paradigm","created":"2025-08-11","cited_by_count":1,"area":null},{"id":"2511.06769","title":"RRTS Dataset: A Benchmark Colonoscopy Dataset from Resource-Limited Settings for Computer-Aided Diagnosis Research","created":"2025-11-10","cited_by_count":1,"area":null},{"id":"2512.03667","title":"Colon-X: Advancing Intelligent Colonoscopy toward Clinical Reasoning","created":"2025-12-03","cited_by_count":1,"area":"lr"},{"id":"2603.22969","title":"FCL-COD: Weakly Supervised Camouflaged Object Detection with Frequency-aware and Contrastive Learning","created":"2026-03-24","cited_by_count":1,"area":null},{"id":"2604.23187","title":"DyABD: The Abdominal Muscle Segmentation in Dynamic MRI Benchmark","created":"2026-04-25","cited_by_count":1,"area":null},{"id":"2604.26232","title":"DepthPilot: From Controllability to Interpretability in Colonoscopy Video Generation","created":"2026-04-29","cited_by_count":1,"area":null},{"id":"2606.20161","title":"ARTEMIS: Agent-guided Reliability-aware Temporal Mask Evolution for Imperfectly Supervised Video Polyp Segmentation","created":"2026-06-18","cited_by_count":1,"area":null},{"id":"2208.03918","title":"Depth Quality-Inspired Feature Manipulation for Efficient RGB-D and Video Salient Object Detection","created":"2022-08-08","cited_by_count":0,"area":null},{"id":"2311.05122","title":"ScribblePolyp: Scribble-Supervised Polyp Segmentation through Dual Consistency Alignment","created":"2023-11-09","cited_by_count":0,"area":null},{"id":"2404.08936","title":"Shifting Spotlight for Co-supervision: A Simple yet Efficient Single-branch Network to See Through Camouflage","created":"2024-04-13","cited_by_count":0,"area":null},{"id":"2409.16774","title":"MixPolyp: Integrating Mask, Box and Scribble Supervision for Enhanced Polyp Segmentation","created":"2024-09-25","cited_by_count":0,"area":null},{"id":"2410.16732","title":"Polyp-E: Benchmarking the Robustness of Deep Segmentation Models via Polyp Editing","created":"2024-10-22","cited_by_count":0,"area":null},{"id":"2508.19705","title":"FreeVPS: Repurposing Training-Free SAM2 for Generalizable Video Polyp Segmentation","created":"2025-08-27","cited_by_count":0,"area":null},{"id":"2511.12810","title":"MSRNet: A Multi-Scale Recursive Network for Camouflaged Object Detection","created":"2025-11-16","cited_by_count":0,"area":null},{"id":"2602.21855","title":"Understanding Annotation Error Propagation and Learning an Adaptive Policy for Expert Intervention in Barrett's Video Segmentation","created":"2026-02-25","cited_by_count":0,"area":null},{"id":"2603.04288","title":"A multi-center analysis of deep learning methods for video polyp detection and segmentation","created":"2026-03-04","cited_by_count":0,"area":null},{"id":"2603.25778","title":"Focus-to-Perceive Representation Learning: A Cognition-Inspired Hierarchical Framework for Endoscopic Video Analysis","created":"2026-03-26","cited_by_count":0,"area":null},{"id":"2604.23542","title":"AusSmoke meets MultiNatSmoke: a fully-labelled diverse smoke segmentation dataset","created":"2026-04-26","cited_by_count":0,"area":null},{"id":"2605.12320","title":"Contrastive Learning under Noisy Temporal Self-Supervision for Colonoscopy Videos","created":"2026-05-12","cited_by_count":0,"area":null},{"id":"2606.31198","title":"Distilling Temporal Coherence into 2D Networks for Transrectal Ultrasound Prostate Video Segmentation","created":"2026-06-30","cited_by_count":0,"area":null},{"id":"2607.06007","title":"OBBSeg: Irregular Lesion Segmentation under Oriented Bounding Box Annotations","created":"2026-07-07","cited_by_count":0,"area":null},{"id":"2607.08203","title":"Metrics or Mirage? An Audit of Evaluation Inconsistencies in Colonoscopy Polyp Segmentation Benchmarks","created":"2026-07-09","cited_by_count":0,"area":null},{"id":"2607.21370","title":"ASTRA-Net: Anatomy-Specific Transfer and Representation Alignment for Drug-Induced Sleep Endoscopy Segmentation","created":"2026-07-23","cited_by_count":0,"area":null},{"id":"2609.15130","title":"woma: a real-time foundation model and its fine-tuned models for endoscopy","created":"2026-09-14","cited_by_count":0,"area":null},{"id":"2609.16672","title":"Lesion-centered 3D mapping of colonoscopy procedures: validation of a hierarchical ensemble pipeline on public benchmark videos","created":"2026-09-15","cited_by_count":0,"area":null},{"id":"2610.02946","title":"When Predicting Nothing Beats SAM 3: Revisiting Evaluation in Video Object Segmentation","created":"2026-10-02","cited_by_count":0,"area":null}],"next_cursor":null}