{"total":250,"rows":[{"id":"2403.14624","title":"MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?","created":"2024-03-21","cited_by_count":586,"area":"mllm"},{"id":"2310.11441","title":"Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V","created":"2023-10-17","cited_by_count":299,"area":"mllm"},{"id":"2309.10020","title":"Multimodal Foundation Models: From Specialists to General-Purpose Assistants","created":"2023-09-18","cited_by_count":247,"area":null},{"id":"2306.16269","title":"RSPrompter: Learning to Prompt for Remote Sensing Instance Segmentation based on Visual Foundation Model","created":"2023-06-28","cited_by_count":181,"area":null},{"id":"2305.13310","title":"Matcher: Segment Anything with One Shot Using All-Purpose Feature Matching","created":"2023-05-22","cited_by_count":142,"area":null},{"id":"2311.15707","title":"SAM-6D: Segment Anything Model Meets Zero-Shot 6D Object Pose Estimation","created":"2023-11-27","cited_by_count":117,"area":null},{"id":"2308.08746","title":"SurgicalSAM: Efficient Class Promptable Surgical Instrument Segmentation","created":"2023-08-17","cited_by_count":104,"area":null},{"id":"2306.16623","title":"The Segment Anything Model (SAM) for Remote Sensing Applications: From Zero to One Shot","created":"2023-06-29","cited_by_count":83,"area":null},{"id":"2401.02955","title":"Open-Vocabulary SAM: Segment and Recognize Twenty-thousand Classes Interactively","created":"2024-01-05","cited_by_count":75,"area":null},{"id":"2402.17726","title":"VRP-SAM: SAM with Visual Reference Prompt","created":"2024-02-27","cited_by_count":75,"area":null},{"id":"2305.08196","title":"A Comprehensive Survey on Segment Anything Model for Vision and Beyond","created":"2023-05-14","cited_by_count":64,"area":null},{"id":"2408.08870","title":"SAM2-UNet: Segment Anything 2 Makes Strong Encoder for Natural and Medical Image Segmentation","created":"2024-08-16","cited_by_count":64,"area":null},{"id":"2404.03653","title":"CoMat: Aligning Text-to-Image Diffusion Model with Image-to-Text Concept Matching","created":"2024-04-04","cited_by_count":61,"area":"diffusion"},{"id":"2505.14671","title":"UniCTokens: Boosting Personalized Understanding and Generation via Unified Concept Tokens","created":"2025-05-20","cited_by_count":56,"area":null},{"id":"2305.16318","title":"Referred by Multi-Modality: A Unified Temporal Transformer for Video Object Segmentation","created":"2023-05-25","cited_by_count":54,"area":null},{"id":"2311.13601","title":"Visual In-Context Prompting","created":"2023-11-22","cited_by_count":52,"area":null},{"id":"2408.07931","title":"Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning","created":"2024-08-15","cited_by_count":47,"area":null},{"id":"2305.11019","title":"Annotation-free Audio-Visual Segmentation","created":"2023-05-18","cited_by_count":46,"area":null},{"id":"2306.06211","title":"A Survey on Segment Anything Model (SAM): Vision Foundation Model Meets Prompt Engineering","created":"2023-05-12","cited_by_count":45,"area":null},{"id":"2310.03059","title":"Point-PEFT: Parameter-Efficient Fine-Tuning for 3D Pre-trained Models","created":"2023-10-04","cited_by_count":42,"area":null},{"id":"2312.09579","title":"MobileSAMv2: Faster Segment Anything to Everything","created":"2023-12-15","cited_by_count":42,"area":null},{"id":"2408.12957","title":"Image Segmentation in Foundation Model Era: A Survey","created":"2024-08-23","cited_by_count":35,"area":"diffusion"},{"id":"2410.06964","title":"Bridge the Points: Graph-based Few-shot Segment Anything Semantically","created":"2024-10-09","cited_by_count":35,"area":null},{"id":"2406.06039","title":"Diving into Underwater: Segment Anything Model Guided Underwater Salient Instance Segmentation and A Large-scale Dataset","created":"2024-06-10","cited_by_count":33,"area":null},{"id":"2504.07958","title":"Detect Anything 3D in the Wild","created":"2025-04-10","cited_by_count":33,"area":null},{"id":"2405.03144","title":"PTQ4SAM: Post-Training Quantization for Segment Anything","created":"2024-05-06","cited_by_count":32,"area":null},{"id":"2409.17874","title":"DarkSAM: Fooling Segment Anything Model to Segment Nothing","created":"2024-09-26","cited_by_count":32,"area":null},{"id":"2311.03774","title":"Meta-Adapter: An Online Few-shot Learner for Vision-Language Model","created":"2023-11-07","cited_by_count":31,"area":"mllm"},{"id":"2312.03502","title":"Improving the Generalization of Segmentation Foundation Model under Distribution Shift via Weakly Supervised Adaptation","created":"2023-12-06","cited_by_count":31,"area":null},{"id":"2409.15278","title":"PixWizard: Versatile Image-to-Image Visual Assistant with Open-Language Instructions","created":"2024-09-23","cited_by_count":31,"area":null},{"id":"2401.17904","title":"Hi-SAM: Marrying Segment Anything Model for Hierarchical Text Segmentation","created":"2024-01-31","cited_by_count":30,"area":null},{"id":"2405.05538","title":"A Survey on Personalized Content Synthesis with Diffusion Models","created":"2024-05-09","cited_by_count":29,"area":"diffusion"},{"id":"2402.03631","title":"CAT-SAM: Conditional Tuning for Few-Shot Adaptation of Segment Anything Model","created":"2024-02-06","cited_by_count":27,"area":null},{"id":"2406.08372","title":"APSeg: Auto-Prompt Network for Cross-Domain Few-Shot Semantic Segmentation","created":"2024-06-12","cited_by_count":26,"area":null},{"id":"2307.00997","title":"RefSAM: Efficiently Adapting Segmenting Anything Model for Referring Video Object Segmentation","created":"2023-07-03","cited_by_count":25,"area":null},{"id":"2504.12597","title":"GeoSense: Evaluating Identification and Application of Geometric Principles in Multimodal Reasoning","created":"2025-04-17","cited_by_count":25,"area":"lr"},{"id":"2310.06311","title":"Improving Compositional Text-to-image Generation with Large Vision-Language Models","created":"2023-10-10","cited_by_count":24,"area":"mllm"},{"id":"2311.11273","title":"Chain of Visual Perception: Harnessing Multimodal Large Language Models for Zero-shot Camouflaged Object Detection","created":"2023-11-19","cited_by_count":22,"area":"mllm"},{"id":"2312.15715","title":"UniRef++: Segment Every Reference Object in Spatial and Temporal Spaces","created":"2023-12-25","cited_by_count":22,"area":null},{"id":"2310.14277","title":"A Survey on Continual Semantic Segmentation: Theory, Challenge, Method and Application","created":"2023-10-22","cited_by_count":21,"area":null},{"id":"2502.06756","title":"SAMRefiner: Taming Segment Anything Model for Universal Mask Refinement","created":"2025-02-10","cited_by_count":20,"area":null},{"id":"2311.14671","title":"SEGIC: Unleashing the Emergent Correspondence for In-Context Segmentation","created":"2023-11-24","cited_by_count":19,"area":null},{"id":"2312.14465","title":"FM-OV3D: Foundation Model-based Cross-modal Knowledge Blending for Open-Vocabulary 3D Detection","created":"2023-12-22","cited_by_count":19,"area":null},{"id":"2410.04842","title":"A Simple Image Segmentation Framework via In-Context Examples","created":"2024-10-07","cited_by_count":19,"area":null},{"id":"2309.12303","title":"PanoVOS: Bridging Non-panoramic and Panoramic Views with Transformer for Video Segmentation","created":"2023-09-21","cited_by_count":18,"area":null},{"id":"2405.18025","title":"Where's Waldo: Diffusion Features for Personalized Segmentation and Retrieval","created":"2024-05-28","cited_by_count":18,"area":null},{"id":"2405.19586","title":"SAM-E: Leveraging Visual Foundation Model with Sequence Imitation for Embodied Manipulation","created":"2024-05-30","cited_by_count":18,"area":null},{"id":"2408.16768","title":"SAM2Point: Segment Any 3D as Videos in Zero-shot and Promptable Manners","created":"2024-08-29","cited_by_count":18,"area":null},{"id":"2508.14153","title":"LENS: Learning to Segment Anything with Unified Reinforced Reasoning","created":"2025-08-19","cited_by_count":18,"area":"lr"},{"id":"2401.13051","title":"PA-SAM: Prompt Adapter SAM for High-Quality Image Segmentation","created":"2024-01-23","cited_by_count":17,"area":null},{"id":"2406.01451","title":"SAM as the Guide: Mastering Pseudo-Label Refinement in Semi-Supervised Referring Expression Segmentation","created":"2024-06-03","cited_by_count":17,"area":null},{"id":"2410.22135","title":"Lightweight Frequency Masker for Cross-Domain Few-Shot Semantic Segmentation","created":"2024-10-29","cited_by_count":17,"area":null},{"id":"2410.02369","title":"Unleashing the Potential of the Diffusion Model in Few-shot Semantic Segmentation","created":"2024-10-03","cited_by_count":16,"area":"diffusion"},{"id":"2410.04960","title":"On Efficient Variants of Segment Anything Model: A Survey","created":"2024-10-07","cited_by_count":16,"area":null},{"id":"2410.05963","title":"Training-Free Open-Ended Object Detection and Segmentation via Attention as Prompts","created":"2024-10-08","cited_by_count":16,"area":null},{"id":"2503.19359","title":"Show and Segment: Universal Medical Image Segmentation via In-Context Learning","created":"2025-03-25","cited_by_count":16,"area":null},{"id":"2310.10912","title":"Towards Training-free Open-world Segmentation via Image Prompt Foundation Models","created":"2023-10-17","cited_by_count":15,"area":null},{"id":"2312.09738","title":"3DAxiesPrompts: Unleashing the 3D Spatial Task Capabilities of GPT-4V","created":"2023-12-15","cited_by_count":15,"area":null},{"id":"2504.12080","title":"DC-SAM: In-Context Segment Anything in Images and Videos via Dual Consistency","created":"2025-04-16","cited_by_count":15,"area":null},{"id":"2305.12659","title":"UVOSAM: A Mask-free Paradigm for Unsupervised Video Object Segmentation via Segment Anything Model","created":"2023-05-22","cited_by_count":14,"area":null},{"id":"2309.12790","title":"NTO3D: Neural Target Object 3D Reconstruction with Segment Anything","created":"2023-09-22","cited_by_count":14,"area":null},{"id":"2404.10322","title":"Domain-Rectifying Adapter for Cross-Domain Few-Shot Segmentation","created":"2024-04-16","cited_by_count":14,"area":null},{"id":"2509.25172","title":"Personalized Vision via Visual In-Context Learning","created":"2025-09-29","cited_by_count":14,"area":null},{"id":"2401.04651","title":"Learning to Prompt Segment Anything Models","created":"2024-01-09","cited_by_count":13,"area":null},{"id":"2406.15764","title":"TP-DRSeg: Improving Diabetic Retinopathy Lesion Segmentation with Explicit Text-Prompts Assisted SAM","created":"2024-06-22","cited_by_count":13,"area":null},{"id":"2407.11464","title":"Crowd-SAM: SAM as a Smart Annotator for Object Detection in Crowded Scenes","created":"2024-07-16","cited_by_count":13,"area":null},{"id":"2503.12781","title":"SAM2 for Image and Video Segmentation: A Comprehensive Survey","created":"2025-03-17","cited_by_count":13,"area":null},{"id":"2312.17116","title":"Generalizable Visual Reinforcement Learning with Segment Anything Model","created":"2023-12-28","cited_by_count":12,"area":null},{"id":"2403.09616","title":"Explore In-Context Segmentation via Latent Diffusion Models","created":"2024-03-14","cited_by_count":12,"area":"diffusion"},{"id":"2405.00256","title":"ASAM: Boosting Segment Anything Model with Adversarial Tuning","created":"2024-05-01","cited_by_count":12,"area":null},{"id":"2407.19435","title":"ASI-Seg: Audio-Driven Surgical Instrument Segmentation with Surgeon Intention Understanding","created":"2024-07-28","cited_by_count":12,"area":null},{"id":"2408.09085","title":"Segment Anything with Multiple Modalities","created":"2024-08-17","cited_by_count":12,"area":null},{"id":"2504.05058","title":"Not All Data Are Unlearned Equally","created":"2025-04-07","cited_by_count":12,"area":"safety"},{"id":"2603.28480","title":"INSID3: Training-Free In-Context Segmentation with DINOv3","created":"2026-03-30","cited_by_count":12,"area":null},{"id":"2410.18195","title":"Personalized Instance-based Navigation Toward User-Specific Objects in Realistic Environments","created":"2024-10-23","cited_by_count":11,"area":null},{"id":"2510.24195","title":"Vanish into Thin Air: Cross-prompt Universal Adversarial Attacks for SAM2","created":"2025-10-28","cited_by_count":11,"area":null},{"id":"2501.16443","title":"Object-Centric World Models from Few-Shot Annotations for Sample-Efficient Reinforcement Learning","created":"2025-01-27","cited_by_count":10,"area":"wm"},{"id":"2503.18623","title":"Training-Free Personalization via Retrieval and Reasoning on Fingerprints","created":"2025-03-24","cited_by_count":10,"area":"lr"},{"id":"2403.06403","title":"PointSeg: A Training-Free Paradigm for 3D Scene Segmentation via Foundation Models","created":"2024-03-11","cited_by_count":9,"area":null},{"id":"2411.17363","title":"SAM-MPA: Applying SAM to Few-shot Medical Image Segmentation using Mask Propagation and Auto-prompting","created":"2024-11-26","cited_by_count":9,"area":null},{"id":"2412.16156","title":"Personalized Representation from Personalized Generation","created":"2024-12-20","cited_by_count":9,"area":null},{"id":"2506.15153","title":"SynPo: Boosting Training-Free Few-Shot Medical Segmentation via High-Quality Negative Prompts","created":"2025-06-18","cited_by_count":9,"area":null},{"id":"2507.02798","title":"No time to train! Training-Free Reference-Based Instance Segmentation","created":"2025-07-03","cited_by_count":9,"area":null},{"id":"2312.14481","title":"SurgicalPart-SAM: Part-to-Whole Collaborative Prompting for Surgical Instrument Segmentation","created":"2023-12-22","cited_by_count":8,"area":null},{"id":"2406.00480","title":"AlignSAM: Aligning Segment Anything Model to Open Context via Reinforcement Learning","created":"2024-06-01","cited_by_count":8,"area":null},{"id":"2407.05324","title":"PICA: Physics-Integrated Clothed Avatar","created":"2024-07-07","cited_by_count":8,"area":null},{"id":"2503.21150","title":"The Devil is in Low-Level Features for Cross-Domain Few-Shot Segmentation","created":"2025-03-27","cited_by_count":8,"area":null},{"id":"2505.21795","title":"SANSA: Unleashing the Hidden Semantics in SAM2 for Few-Shot Segmentation","created":"2025-05-27","cited_by_count":8,"area":null},{"id":"2506.14271","title":"Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment","created":"2025-06-17","cited_by_count":8,"area":null},{"id":"2507.09577","title":"Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation","created":"2025-07-13","cited_by_count":8,"area":null},{"id":"2406.03723","title":"Gear-NeRF: Free-Viewpoint Rendering and Tracking with Motion-aware Spatio-Temporal Sampling","created":"2024-06-06","cited_by_count":7,"area":null},{"id":"2411.06971","title":"MapSAM: Adapting Segment Anything Model for Automated Feature Detection in Historical Maps","created":"2024-11-11","cited_by_count":7,"area":null},{"id":"2411.15288","title":"There is no SAMantics! Exploring SAM as a Backbone for Visual Understanding Tasks","created":"2024-11-22","cited_by_count":7,"area":null},{"id":"2506.07376","title":"Adapter Naturally Serves as Decoupler for Cross-Domain Few-Shot Semantic Segmentation","created":"2025-06-09","cited_by_count":7,"area":null},{"id":"2510.10524","title":"Unified Open-World Segmentation with Multi-Modal Prompts","created":"2025-10-12","cited_by_count":7,"area":null},{"id":"2403.10971","title":"Task-Aware Low-Rank Adaptation of Segment Anything Model","created":"2024-03-16","cited_by_count":6,"area":null},{"id":"2409.04714","title":"Unleashing the Power of Generic Segmentation Models: A Simple Baseline for Infrared Small Target Detection","created":"2024-09-07","cited_by_count":6,"area":null},{"id":"2409.06821","title":"Sam2Rad: A Segmentation Model for Medical Images with Learnable Prompts","created":"2024-09-10","cited_by_count":6,"area":null},{"id":"2411.13317","title":"Teaching VLMs to Localize Specific Objects from In-context Examples","created":"2024-11-20","cited_by_count":6,"area":"mllm"},{"id":"2505.24182","title":"Seeing is Not Reasoning: MVPBench for Graph-based Evaluation of Multi-path Visual Physical CoT","created":"2025-05-30","cited_by_count":6,"area":"lr"}],"next_cursor":"100"}