Fine-Grained Visual Perception

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14 papers in the last four weeks, up 250% on the four weeks before. 0.1% of all new papers.

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ContourVLA: A Closed-Loop Perception-Action Contour Policy for Generalized Referring Expression Segmentation
Oct 8, 2026Ruicheng Zhang, Kaiwen Shen, Jiaqi Hou +6Referring Expression Segmentation Referring Image Segmentation
Sun Yat-sen University · Tsinghua University · The Chinese University of Hong Kong, Shenzhen +1
Mixture of Layers: Dynamic Layer Routing for Visual Reasoning
Oct 7, 2026Jeonghwan Kim, Sofia Stoica, Jiwan Chung +5VLM Reasoning Large Vision-Language Models
University of Illinois Urbana-Champaign · Yonsei University · Meta Reality Labs
A Stevens's Power Law Check-up of GPT-5.5's Implicit Reading of Visual Encoding
Oct 6, 2026Kaichun Yang, Jian ChenVLM Evaluation Chart Understanding
The Ohio State University
Unlocking Fine-Grained Perception in CLIP via Structurally-Aware Latent Masked Modeling
Oct 6, 2026Juntong Li, Lingwei Dang, Haomin Wu +3VLM Adaptation Dense Prediction
School of Software Engineering, South China University of Technology
EviRover: Reinforcing Agentic Perception Beyond a Glance
Sep 30, 2026Kaixuan Fan, Kaituo Feng, Tianshuo Peng +4Tool-Using Vision-Language Agents Active Visual Perception
MMLab, The Chinese University of Hong Kong · Fudan University
GroundingPI: A Grounding Foundation Model towards Physical Intelligence with Visual Primitives
Sep 30, 2026Qize Yu, Lianrui Fan, Boyu Chen +23Vision-Language Grounding VLMs for Robotics
XPeng Inc. · Peking University · The University of Hong Kong +4
Seeing Is Not Addressing: Auditing Linguistic Access to Frozen Visual Geometry
Sep 29, 2026Woosang Jeon, Jiwon Yang, Soo Chung +1Vision-Language Models Vision-Language Grounding
Seoul National University
EviViT: Evidence-Adaptive Vision Transformers for Fine-Grained Perception
Sep 29, 2026Yaoxin Niu, Zhangquan Chen, Yang Zhang +5VLM Adaptation Efficient ViTs
Tsinghua University · Peng Cheng Laboratory · The Hong Kong University of Science and Technology +3
Why MLLMs Struggle to Count: Overcoming Individuation and Aggregation Bottlenecks with ConvStack
Sep 29, 2026Liwei Che, Yihao Quan, Sen Fang +4Object Counting Multimodal Large Language Models
Department of Computer Science, Rutgers University · Department of Computer Science, University of Washington
Hard Vision, Easy Vision: What GPT-6 Astra Reveals Across Computer Vision
Sep 28, 2026Hanoona Rasheed, Mohammed Irfan Kurpath, Bin Ren +3Vision Foundation Models Large Vision-Language Models
Mohamed bin Zayed University of Artificial Intelligence · Apertix
VD-DeepStack: Bridging Visual Comparison and Language Reasoning for Few-Shot Anomaly Detection
Sep 28, 2026Mengyang Zhao, Zhuolin He, Haiyang Yu +9Few-Shot Anomaly Detection Visual Reasoning
Fudan University · University of Southern California · Fuzhou University +1
Evidence-Aligned Multimodal On-Policy Self-Distillation for Fine-Grained Visual Understanding
Sep 28, 2026Nanxing Hu, Qiwei Yan, Jinchao Zhang +1On-Policy Self-Distillation VLM Distillation
Beihang University · University of the Chinese Academy of Sciences
Not All Confusion Is Equal: A Source-Aware Uncertainty Diagnosis for Fine-Grained Aircraft Detection
Sep 24, 2026Hai Huang, Helmut MayerObject Detection Fine-Grained Visual Perception
Chair of Visual Computing, Institute for Applied Computer Science, Universität der Bundeswehr München, Germany
BAS-OPD: Budget-Aware Selective On-Policy Self-Distillation for Fine-Grained Multimodal Perception
Sep 22, 2026Zihan Chen, Hengguang Zhou, Yuan Kang +5VLM Distillation Multimodal Large Language Models
HFIPS, Chinese Academy of Sciences · University of Science and Technology of China · University of California, Los Angeles
Look Where It Counts: A Free, Label-Free Visual Evidence Signal for Fine-Grained Vision-Language Reasoning
Sep 21, 2026Santi Ram Tiwari, Nihal Naik, Devbrat Pandey +1Vision-Language Grounding VLM Reasoning
KGraph AI Solutions Pvt. Ltd. Bangalore, India – 560016
Region-Level Policy Optimization for Fine-grained MLLM Perception
Sep 17, 2026Yuheng Shi, Xiaohuan Pei, Minjing Dong +1Efficient VLM Inference Large Vision-Language Models
University of Sydney · City University of Hong Kong
CoralscapesV2: Panoptic and Fine-Grained Visual Scene Understanding in Coral Reefs
Sep 14, 2026Jonathan Sauder, Thomas Ruckli, Gabrielė Strodomskytė +17Panoptic Segmentation Instance Segmentation
MIT · EPFL · University of Djibouti +7
HiPerViT: A Hierarchical Perceiver-Vision Transformer Architecture for Multi-Scale Texture Recognition
Sep 11, 2026João Pedro C. A. de Sá, Odemir Martinez BrunoVisual Representation Learning Vision Transformer
Institute of Mathematics and Computer Sciences (ICMC), University of São Paulo (USP), Avenida Trabalhador São-carlense, 400, São Carlos, SP 13566-590, Brazil · São Carlos Institute of Physics (IFSC), University of São Paulo (USP), Avenida Trabalhador São-carlense, 400, São Carlos, SP 13566-590, Brazil
ConCA: Concentration-Aware Channel Attention for Fine-Grained Visual Recognition
Aug 31, 2026Yu-Sheng Liu, Yu-Chen TungChannel Attention Fine-Grained Image Classification
Department of Physics, National Kaohsiung Normal University, Kaohsiung, 824, Taiwan
Evaluating 2D and 3D-Aware Vision Foundation Models for Vehicle Attribute Recognition
Aug 30, 2026Alexandre V. Delazeri, Gabriel E. Lima, Eduil Nascimento +2Vision Foundation Models Fine-Grained Visual Perception
Department of Informatics, Federal University of Paraná, Curitiba, Brazil · Department of Technological Development and Quality, Paraná Military Police, Curitiba, Brazil · Graduate Program in Informatics, Pontifical Catholic University of Paraná, Curitiba, Brazil
More Accurate, Less Human: Gestalt Grouping in Vision Models
Aug 10, 2026Sudhanva Manjunath Athreya, Sai Phani Kumar MalladiVLM Evaluation Data Visualization
Siemens AG · University of Utah Siemens AG
GRASP: Granularity-Aware Region Alignment and Semantic Prototype Learning for Fine-Grained Cross-Modal Understanding in Drone Views
Aug 10, 2026Jiahui Cui, Yan Zhao, Kan Wei +4Vision-Language Models Fine-Grained Image Retrieval
Aerospace Information Research Institute, Chinese Academy of Sciences · Key Laboratory of Target Cognition and Application Technology (TCAT), Beijing, China · University of Chinese Academy of Sciences, Beijing, China +1
Credit the Right Box: Marginal Contribution Assignment for Structured Visual Perception
Aug 2, 2026Xinheng Han, Jianfei Wang, Yu Chen +4Multimodal Grounding Group Relative Policy Optimization
School of Automation, Beijing Institute of Technology · Amap, Alibaba Group
Location-Aware Fine-Grained Representation Learning for Medical Vision Foundation Models
Aug 2, 2026Myeongkyun Kang, Yanting Yang, Xiaoxiao LiMedical Imaging Foundation Models Medical Image Grounding
The University of British Columbia · Vector Institute
Foveated Probes Recover Localized Binding Information in Vision Foundation Models
Aug 1, 2026Mateusz Michalkiewicz, Mahsa Baktashmotlagh, Guha BalakrishnanVisual Representation Learning Vision Foundation Models
Rice University, Houston, TX, USA · The University of Queensland, Brisbane, QLD, Australia
EEG-EditBench: Probing Visual Information in EEG-Image Retrieval Models with Controlled Image Edits
Jul 30, 2026Kaifan Zhang, Lihuo He, Yuqi Ji +4EEG Decoding EEG-Based Visual Decoding
School of Electronic Engineering, Xidian University, Xi’an, China · School of Software, Tsinghua University, Beijing, China · Chongqing University of Posts and Telecommunications, Chongqing, China
Fine-Grained Food Image Understanding via Target-Aware Data Alignment
Jul 28, 2026Jui-Feng Chi, Wei-Lun Chu, Bruce Coburn +2Fine-Grained Image Retrieval Fine-Grained Image Classification
Elmore Family School of Electrical and Computer Engineering Purdue University, West Lafayette, IN, USA
PerceptionBench: Evaluating Atomic Visual Perception in Multimodal Large Language Models
Jul 27, 2026Zichao Lin, Yifeng Xie, Bowen Qu +30Object Hallucination in VLMs Multimodal Large Language Models
Moonshot AI
Fine-grained CLIP fine-tuning with self-annotated region alignment
Jul 15, 2026Chenyang Zhao, Wei Lin, Antoni B. Chan +1VLM Adaptation Vision-Language Grounding
Department of Computer Science, City University of Hong Kong · Division of Social Science, Hong Kong University of Science & Technology
Beyond Color Geometry: Evaluating Human-Like Color Representations in Vision Models
Jul 15, 2026Ayan Igali, Pakizar ShamoiVisual Representation Learning Fine-Grained Visual Perception
School of Information Technology and Engineering Kazakh–British Technical University Almaty, Kazakhstan

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ContourVLA: A Closed-Loop Perception-Action Contour Policy for Generalized Referring Expression Segmentation

Ruicheng Zhang, Kaiwen Shen, Jiaqi Hou, Shuhan Yang+5

Sun Yat-sen University · Tsinghua University · The Chinese University of Hong Kong, Shenzhen+1

Referring Expression Segmentation Referring Image Segmentation Vision-Language-Action Models RL for VLMs Fine-Grained Visual Perception

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Generalized referring expression segmentation (GRES) requires dynamically balancing high-level semantics for identifying a variable number of language-specified referents with fine-grained visual evidence for precise boundary delineation. This requirement challenges existing cascaded vision-language architectures, which typically rely on static feature interfaces and single-pass mask prediction, limiting adaptive perception and geometric correction. We introduce ContourVLA, a vision-language-action policy that recasts GRES as a closed-loop visuomotor process, in which editable contours serve as explicit policy states that condition multimodal perception and are updated by geometric action chunks. Evolution-Aware Semantic Scheduling (EASS) couples contour-guided bidirectional boundary sampling with state-conditioned routing of multilevel multimodal features, adapting perception to each contour state. Following supervised initialization, Dustbin-Augmented Entropic Credit Transport GRPO (DECT-GRPO) jointly optimizes discrete grounding and continuous contour actions with instance-level credits. Its rollout rewards and credits are derived from soft prediction-target correspondences that account for false positives and missed targets. ContourVLA improves gIoU over the strongest evaluated baselines by 8.7, 2.8, and 2.7 points on gRefCOCO val, testA, and testB, respectively, and achieves the highest mIoU across all eight RefCOCO, RefCOCO+, and RefCOCOg splits.

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