{"total":178,"rows":[{"id":"2304.00685","title":"Vision-Language Models for Vision Tasks: A Survey","created":"2023-04-03","cited_by_count":839,"area":"mllm"},{"id":"2306.01567","title":"Segment Anything in High Quality","created":"2023-06-02","cited_by_count":376,"area":null},{"id":"2303.11797","title":"CAT-Seg: Cost Aggregation for Open-Vocabulary Semantic Segmentation","created":"2023-03-21","cited_by_count":219,"area":null},{"id":"2308.02487","title":"Convolutions Die Hard: Open-Vocabulary Segmentation with Single Frozen Convolutional CLIP","created":"2023-08-04","cited_by_count":201,"area":null},{"id":"2312.01597","title":"SCLIP: Rethinking Self-Attention for Dense Vision-Language Inference","created":"2023-12-04","cited_by_count":170,"area":null},{"id":"2312.00195","title":"Raising the Bar of AI-generated Image Detection with CLIP","created":"2023-11-30","cited_by_count":164,"area":"mllm"},{"id":"2308.11681","title":"VadCLIP: Adapting Vision-Language Models for Weakly Supervised Video Anomaly Detection","created":"2023-08-22","cited_by_count":123,"area":"mllm"},{"id":"2306.01293","title":"LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning","created":"2023-06-02","cited_by_count":107,"area":null},{"id":"2404.05231","title":"PromptAD: Learning Prompts with only Normal Samples for Few-Shot Anomaly Detection","created":"2024-04-08","cited_by_count":98,"area":null},{"id":"2305.07304","title":"CLIP-Count: Towards Text-Guided Zero-Shot Object Counting","created":"2023-05-12","cited_by_count":83,"area":"mllm"},{"id":"2503.06661","title":"AA-CLIP: Enhancing Zero-shot Anomaly Detection via Anomaly-Aware CLIP","created":"2025-03-09","cited_by_count":73,"area":null},{"id":"2303.17811","title":"Zero-shot Referring Image Segmentation with Global-Local Context Features","created":"2023-03-31","cited_by_count":61,"area":null},{"id":"2307.09220","title":"A Survey on Open-Vocabulary Detection and Segmentation: Past, Present, and Future","created":"2023-07-18","cited_by_count":61,"area":null},{"id":"2407.08268","title":"Explore the Potential of CLIP for Training-Free Open Vocabulary Semantic Segmentation","created":"2024-07-11","cited_by_count":61,"area":"mllm"},{"id":"2411.02545","title":"TripletCLIP: Improving Compositional Reasoning of CLIP via Synthetic Vision-Language Negatives","created":"2024-11-04","cited_by_count":58,"area":null},{"id":"2311.07042","title":"Open-Vocabulary Video Anomaly Detection","created":"2023-11-13","cited_by_count":57,"area":null},{"id":"2407.12276","title":"VCP-CLIP: A visual context prompting model for zero-shot anomaly segmentation","created":"2024-07-17","cited_by_count":50,"area":"mllm"},{"id":"2403.01849","title":"One Prompt Word is Enough to Boost Adversarial Robustness for Pre-trained Vision-Language Models","created":"2024-03-04","cited_by_count":48,"area":"mllm"},{"id":"2311.17776","title":"One-Shot Open Affordance Learning with Foundation Models","created":"2023-11-29","cited_by_count":45,"area":null},{"id":"2311.16241","title":"SemiVL: Semi-Supervised Semantic Segmentation with Vision-Language Guidance","created":"2023-11-27","cited_by_count":41,"area":null},{"id":"2411.09219","title":"Harnessing Vision Foundation Models for High-Performance, Training-Free Open Vocabulary Segmentation","created":"2024-11-14","cited_by_count":39,"area":null},{"id":"2407.20171","title":"Diffusion Feedback Helps CLIP See Better","created":"2024-07-29","cited_by_count":38,"area":"diffusion"},{"id":"2407.02880","title":"Knowledge Composition using Task Vectors with Learned Anisotropic Scaling","created":"2024-07-03","cited_by_count":37,"area":null},{"id":"2311.01723","title":"Towards Calibrated Robust Fine-Tuning of Vision-Language Models","created":"2023-11-03","cited_by_count":35,"area":"mllm"},{"id":"2408.12957","title":"Image Segmentation in Foundation Model Era: A Survey","created":"2024-08-23","cited_by_count":35,"area":"diffusion"},{"id":"2305.06061","title":"Visual Tuning","created":"2023-05-10","cited_by_count":34,"area":null},{"id":"2408.10123","title":"Learning Precise Affordances from Egocentric Videos for Robotic Manipulation","created":"2024-08-19","cited_by_count":34,"area":null},{"id":"2403.15132","title":"Transfer CLIP for Generalizable Image Denoising","created":"2024-03-22","cited_by_count":29,"area":null},{"id":"2411.15851","title":"ResCLIP: Residual Attention for Training-free Dense Vision-language Inference","created":"2024-11-24","cited_by_count":29,"area":"mllm"},{"id":"2308.07706","title":"Exploring Transfer Learning in Medical Image Segmentation using Vision-Language Models","created":"2023-08-15","cited_by_count":28,"area":"mllm"},{"id":"2409.11884","title":"Out-of-Distribution Detection: A Task-Oriented Survey of Recent Advances","created":"2024-09-18","cited_by_count":26,"area":null},{"id":"2306.06289","title":"SegViTv2: Exploring Efficient and Continual Semantic Segmentation with Plain Vision Transformers","created":"2023-06-09","cited_by_count":25,"area":null},{"id":"2504.03193","title":"Mamba as a Bridge: Where Vision Foundation Models Meet Vision Language Models for Domain-Generalized Semantic Segmentation","created":"2025-04-04","cited_by_count":24,"area":"mllm"},{"id":"2509.18096","title":"Seg4Diff: Unveiling Open-Vocabulary Segmentation in Text-to-Image Diffusion Transformers","created":"2025-09-22","cited_by_count":24,"area":"diffusion"},{"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":"2311.14064","title":"HGCLIP: Exploring Vision-Language Models with Graph Representations for Hierarchical Understanding","created":"2023-11-23","cited_by_count":21,"area":"mllm"},{"id":"2403.08108","title":"TaskCLIP: Extend Large Vision-Language Model for Task Oriented Object Detection","created":"2024-03-12","cited_by_count":21,"area":"mllm"},{"id":"2403.10801","title":"Securely Fine-tuning Pre-trained Encoders Against Adversarial Examples","created":"2024-03-16","cited_by_count":21,"area":null},{"id":"2407.09033","title":"Textual Query-Driven Mask Transformer for Domain Generalized Segmentation","created":"2024-07-12","cited_by_count":21,"area":"mllm"},{"id":"2308.07605","title":"SGDiff: A Style Guided Diffusion Model for Fashion Synthesis","created":"2023-08-15","cited_by_count":20,"area":"diffusion"},{"id":"2312.02021","title":"Strong but simple: A Baseline for Domain Generalized Dense Perception by CLIP-based Transfer Learning","created":"2023-12-04","cited_by_count":20,"area":"mllm"},{"id":"2408.03574","title":"Teach CLIP to Develop a Number Sense for Ordinal Regression","created":"2024-08-07","cited_by_count":20,"area":null},{"id":"2401.05806","title":"CLIP-Driven Semantic Discovery Network for Visible-Infrared Person Re-Identification","created":"2024-01-11","cited_by_count":19,"area":null},{"id":"2409.19846","title":"Towards Open-Vocabulary Semantic Segmentation Without Semantic Labels","created":"2024-09-30","cited_by_count":19,"area":"mllm"},{"id":"2303.02344","title":"Improving Audio-Visual Video Parsing with Pseudo Visual Labels","created":"2023-03-04","cited_by_count":18,"area":null},{"id":"2405.04788","title":"SemiCD-VL: Visual-Language Model Guidance Makes Better Semi-supervised Change Detector","created":"2024-05-08","cited_by_count":18,"area":"mllm"},{"id":"2410.15385","title":"LoRA-IR: Taming Low-Rank Experts for Efficient All-in-One Image Restoration","created":"2024-10-20","cited_by_count":18,"area":"moe"},{"id":"2505.14361","title":"Vision-Language Modeling Meets Remote Sensing: Models, Datasets and Perspectives","created":"2025-05-20","cited_by_count":18,"area":"mllm"},{"id":"2406.00670","title":"Cascade-CLIP: Cascaded Vision-Language Embeddings Alignment for Zero-Shot Semantic Segmentation","created":"2024-06-02","cited_by_count":17,"area":"mllm"},{"id":"2411.14723","title":"Effective SAM Combination for Open-Vocabulary Semantic Segmentation","created":"2024-11-22","cited_by_count":17,"area":null},{"id":"2301.12171","title":"ZegOT: Zero-shot Segmentation Through Optimal Transport of Text Prompts","created":"2023-01-28","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":"2409.06809","title":"DetailCLIP: Detail-Oriented CLIP for Fine-Grained Tasks","created":"2024-09-10","cited_by_count":15,"area":"mllm"},{"id":"2304.07547","title":"TagCLIP: Improving Discrimination Ability of Open-Vocabulary Semantic Segmentation","created":"2023-04-15","cited_by_count":14,"area":null},{"id":"2410.15397","title":"IPO: Interpretable Prompt Optimization for Vision-Language Models","created":"2024-10-20","cited_by_count":14,"area":"mllm"},{"id":"2401.02402","title":"3D Open-Vocabulary Panoptic Segmentation with 2D-3D Vision-Language Distillation","created":"2024-01-04","cited_by_count":13,"area":null},{"id":"2403.12455","title":"CLIP-VIS: Adapting CLIP for Open-Vocabulary Video Instance Segmentation","created":"2024-03-19","cited_by_count":13,"area":null},{"id":"2404.02157","title":"Segment Any 3D Object with Language","created":"2024-04-02","cited_by_count":13,"area":null},{"id":"2407.05352","title":"Exploring Phrase-Level Grounding with Text-to-Image Diffusion Model","created":"2024-07-07","cited_by_count":13,"area":"diffusion"},{"id":"2504.04893","title":"SCAM: A Real-World Typographic Robustness Evaluation for Multimodal Foundation Models","created":"2025-04-07","cited_by_count":13,"area":"mllm"},{"id":"2310.15676","title":"Recent Advances in Multi-modal 3D Intelligence: A Comprehensive Survey and Evaluation","created":"2023-10-24","cited_by_count":12,"area":null},{"id":"2505.19503","title":"Locality-Aware Zero-Shot Human-Object Interaction Detection","created":"2025-05-26","cited_by_count":12,"area":"mllm"},{"id":"2307.09815","title":"LDP: Language-driven Dual-Pixel Image Defocus Deblurring Network","created":"2023-07-19","cited_by_count":11,"area":null},{"id":"2504.12104","title":"Logits DeConfusion with CLIP for Few-Shot Learning","created":"2025-04-16","cited_by_count":11,"area":null},{"id":"2504.09480","title":"Vision-Language Model for Object Detection and Segmentation: A Review and Evaluation","created":"2025-04-13","cited_by_count":10,"area":"mllm"},{"id":"2310.02296","title":"CLIP Is Also a Good Teacher: A New Learning Framework for Inductive Zero-shot Semantic Segmentation","created":"2023-10-03","cited_by_count":9,"area":null},{"id":"2401.03522","title":"Text-Driven Traffic Anomaly Detection with Temporal High-Frequency Modeling in Driving Videos","created":"2024-01-07","cited_by_count":9,"area":null},{"id":"2403.09620","title":"PosSAM: Panoptic Open-vocabulary Segment Anything","created":"2024-03-14","cited_by_count":9,"area":null},{"id":"2403.14183","title":"OTSeg: Multi-prompt Sinkhorn Attention for Zero-Shot Semantic Segmentation","created":"2024-03-21","cited_by_count":9,"area":null},{"id":"2409.08468","title":"Generalization Boosted Adapter for Open-Vocabulary Segmentation","created":"2024-09-13","cited_by_count":9,"area":"mllm"},{"id":"2504.09203","title":"AerOSeg: Harnessing SAM for Open-Vocabulary Segmentation in Remote Sensing Images","created":"2025-04-12","cited_by_count":9,"area":null},{"id":"2506.02439","title":"Video-Level Language-Driven Video-Based Visible-Infrared Person Re-Identification","created":"2025-06-03","cited_by_count":9,"area":null},{"id":"2405.15169","title":"Bring Adaptive Binding Prototypes to Generalized Referring Expression Segmentation","created":"2024-05-24","cited_by_count":8,"area":null},{"id":"2411.10922","title":"Exploiting VLM Localizability and Semantics for Open Vocabulary Action Detection","created":"2024-11-17","cited_by_count":8,"area":null},{"id":"2303.00973","title":"Image Labels Are All You Need for Coarse Seagrass Segmentation","created":"2023-03-02","cited_by_count":7,"area":null},{"id":"2402.03251","title":"CLIP Can Understand Depth","created":"2024-02-05","cited_by_count":7,"area":null},{"id":"2411.12044","title":"ITACLIP: Boosting Training-Free Semantic Segmentation with Image, Text, and Architectural Enhancements","created":"2024-11-18","cited_by_count":7,"area":"mllm"},{"id":"2501.16065","title":"CILP-FGDI: Exploiting Vision-Language Model for Generalizable Person Re-Identification","created":"2025-01-27","cited_by_count":7,"area":"mllm"},{"id":"2502.12513","title":"RealSyn: An Effective and Scalable Multimodal Interleaved Document Transformation Paradigm","created":"2025-02-18","cited_by_count":7,"area":null},{"id":"2507.10095","title":"FIX-CLIP: Dual-Branch Hierarchical Contrastive Learning via Synthetic Captions for Better Understanding of Long Text","created":"2025-07-14","cited_by_count":7,"area":null},{"id":"2403.06793","title":"Boosting Image Restoration via Priors from Pre-trained Models","created":"2024-03-11","cited_by_count":6,"area":"diffusion"},{"id":"2403.08426","title":"Language-Driven Visual Consensus for Zero-Shot Semantic Segmentation","created":"2024-03-13","cited_by_count":6,"area":"mllm"},{"id":"2304.06212","title":"[CLS] Token is All You Need for Zero-Shot Semantic Segmentation","created":"2023-04-13","cited_by_count":5,"area":"mllm"},{"id":"2404.05667","title":"AlignZeg: Mitigating Objective Misalignment for Zero-shot Semantic Segmentation","created":"2024-04-08","cited_by_count":5,"area":null},{"id":"2406.06908","title":"UVIS: Unsupervised Video Instance Segmentation","created":"2024-06-11","cited_by_count":5,"area":null},{"id":"2412.11464","title":"High-Quality Mask Tuning Matters for Open-Vocabulary Segmentation","created":"2024-12-16","cited_by_count":5,"area":"mllm"},{"id":"2511.12639","title":"Medical Knowledge Intervention Prompt Tuning for Medical Image Classification","created":"2025-11-16","cited_by_count":5,"area":"mllm"},{"id":"2302.06039","title":"Predicting Class Distribution Shift for Reliable Domain Adaptive Object Detection","created":"2023-02-13","cited_by_count":4,"area":null},{"id":"2308.12960","title":"Towards Realistic Zero-Shot Classification via Self Structural Semantic Alignment","created":"2023-08-24","cited_by_count":4,"area":"mllm"},{"id":"2312.12463","title":"Open Vocabulary Semantic Scene Sketch Understanding","created":"2023-12-18","cited_by_count":4,"area":null},{"id":"2407.01220","title":"Fast and Efficient: Mask Neural Fields for 3D Scene Segmentation","created":"2024-07-01","cited_by_count":4,"area":null},{"id":"2409.18372","title":"You Only Speak Once to See","created":"2024-09-27","cited_by_count":4,"area":null},{"id":"2501.09688","title":"Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation","created":"2025-01-16","cited_by_count":4,"area":null},{"id":"2501.16222","title":"SPECIAL: Zero-shot Hyperspectral Image Classification With CLIP","created":"2025-01-27","cited_by_count":4,"area":null},{"id":"2503.10779","title":"The Power of One: A Single Example is All it Takes for Segmentation in VLMs","created":"2025-03-13","cited_by_count":4,"area":"mllm"},{"id":"2504.06389","title":"SemiDAViL: Semi-supervised Domain Adaptation with Vision-Language Guidance for Semantic Segmentation","created":"2025-04-08","cited_by_count":4,"area":null},{"id":"2602.20423","title":"MedCLIPSeg: Probabilistic Vision-Language Adaptation for Data-Efficient and Generalizable Medical Image Segmentation","created":"2026-02-23","cited_by_count":4,"area":"mllm"},{"id":"2302.14163","title":"A Language-Guided Benchmark for Weakly Supervised Open Vocabulary Semantic Segmentation","created":"2023-02-27","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":"2308.12757","title":"PartSeg: Few-shot Part Segmentation via Part-aware Prompt Learning","created":"2023-08-24","cited_by_count":3,"area":null}],"next_cursor":"100"}