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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P $^2$ -DPO: Grounding Hallucination in Perceptual Processing via Calibration Direct Preference Optimization
Jun 2, 2026Ruipeng Zhang, Zhihao Li, Haozhang Yuan +2VLM Robustness Direct Preference Optimization
Guangdong Provincial Key Laboratory of Computational AI Models and Cognitive Intelligence, School of Computer Science & Engineering, South China University of Technology · Pazhou Lab, Guangzhou, China · Engineering Research Center of the Ministry of Education on Health Intelligent Perception and Paralleled Digital-Human, Guangzhou, China
FineGen: A VLM-based Multi-Agent Framework for Fine-Grained Image-Text Dataset Construction
Jun 2, 2026Chang Kong, Yuebing Li, Peng Mo +2Synthetic Data Augmentation Vision-Language Models
Shenzhen Polytechnic University, Shenzhen, China · Institute of Applied Artificial Intelligence of the Guangdong-Hong Kong Macao2026 Greater Bay Area, Shenzhen, China · Shenzhen University, China
Generalization Limits in Vehicle Re-Identification
Jun 1, 2026Anis Yassine Ben Mabrouk, Antoine Tadros, Rafael Grompone von Gioi +3Fine-Grained Visual Perception Cross-Dataset Generalization
CB · Universit´e Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli · CMLA, LIGM +3
CoSTL: Comprehensive Spatial-Temporal Representation Learning for Moment Retrieval and Highlight Detection
May 31, 2026Xin Dong, Wenjia Geng, Wenfeng Deng +1Temporal Video Grounding Video Representation Learning
Shenzhen International Graduate School, Tsinghua University · Pengcheng Laboratory
UniVerse: A Unified Modulation Framework for Segmentation-Free,Disentangled Multi-Concept Personalization
May 29, 2026Quynh Phung, Sandesh Ghimire, Minsi Hu +2Diffusion Transformer Image Generation
University of Maryland, College Park · Qualcomm Technologies, Inc.
SOCO: Benchmarking Semantic Object Correspondence in Vision Foundation Models
May 29, 2026Olaf Dünkel, Basavaraj Sunagad, Haoran Wang +3VLM Evaluation Semantic Correspondence
Max Planck Institute for Informatics, SIC · CISPA Helmholtz Center for Information Security · University of Freiburg
iVGR: Internalizing Visually Grounded Reasoning for MLLMs with Reinforcement Learning
May 29, 2026Chang-Bin Zhang, Yujie Zhong, Qiang Zhang +1Large Vision-Language Models Vision-Language Grounding
Visual AI Lab, The University of Hong Kong · Independent Researcher · University of Science and Technology of China
DiffSpot: Can VLMs Spot Fine-Grained Visual Differences in Web Interfaces?
May 28, 2026Linhao Zhang, Aiwei Liu, Yuan Liu +1VLM Evaluation Fine-Grained Visual Perception
WeChat AI, Tencent Inc.
DV-SFT: Direct Vision Supervision for Fine-Grained Visual Understanding
May 26, 2026Jianfei Zhao, Feng Zhang, Xin Sun +3Supervised Fine-Tuning Vision-Language Models
School of Computer Science and Technology, Beijing Institute of Technology · 2Zhongguancun Academy · 5Southeast Academy of Information Technology, Beijing Institute of Technology +2
VisualNeedle: Benchmarking Active Visual Search in Information-Dense Scenes
May 25, 2026Jingru Chen, Yiming Liu, Mingtao Chen +5VLM Evaluation Tool Use in VLMs
Hunyuan, Tencent · Peking University · Zhejiang University
PGT: Procedurally Generated Tasks for improving visual grounding in MLLMs
May 22, 2026Rim Assouel, Amir Bar, Michal Drozdzal +1Visual Spatial Reasoning Synthetic Data Generation
1Mila - Québec AI Institute · 4McGill University · 3FAIR at Meta Superintelligence Labs +2
Seeing without Looking: Do Vision-Language Benchmarks Really Test Vision?
May 21, 2026Zixuan Lan, Luzhe Sun, Matthew R. Walter +1VLM Evaluation VLM Interpretability
University of Chicago · Toyota Technological Institute at Chicago · Stony Brook University
Towards UAV Detection in the Real World: A New Multispectral Dataset UAVNet-MS and a New Method
May 20, 2026Yihang Luo, Jun Chen, Chao Xiao +13Multispectral Object Detection Small Object Detection
College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China · Aviation University of Air Force, China · Sun Yat-sen University, China
FruitEnsemble: MLLM-Guided Arbitration for Heterogeneous ensemble in Fine-Grained Fruit Recognition
May 20, 2026Enhui Yu, Junhui Li, Ruitong Lu +2Agricultural Image Analysis Ensemble Learning
University of Science and Technology Liaoning · Chuzhou University · Yeshiva University
Beyond Binary Success: A Diagnostic Meta-Evaluation Framework for Fine-Grained Manipulation
May 19, 2026He-Yang Xu, Pengyuan Zhang, Zongyuan Ge +5VLM Evaluation Robotic Manipulation
Southeast University, China · Monash University, Australia · Xiaomi EV, China +2
Vision-OPD: Learning to See Fine Details for Multimodal LLMs via On-Policy Self-Distillation
May 18, 2026Qianhao Yuan, Jie Lou, Xing Yu +4Multimodal Large Language Models On-Policy Distillation
Chinese Information Processing Laboratory, Institute of Software, Chinese Academy of Sciences · University of Chinese Academy of Sciences · Xiaohongshu Inc.
A Large-Scale Study on the Accuracy vs Cost Trade-offs of Training and Evaluation Settings in Fine-Grained Image Recognition
May 18, 2026Edwin Arkel Rios, Augusto Christian Surya, Oswin Gosal +5Data Augmentation Cost-Aware Inference
National Yang Ming Chiao Tung University, Taiwan · National Tsing Hua University, Taiwan
Collision-Resistant Single-Pass Method for Unsupervised Fine-Grained Image Hashing
May 18, 2026Anh-Kiet Duong, Petra Gomez-Krämer, Jean-Michel CarozzaFine-Grained Image Retrieval Image Retrieval
L3i Laboratory, La Rochelle University, 17042 La Rochelle Cedex 1, France · LIENSs Laboratory, La Rochelle University, 17042 La Rochelle Cedex 1, France
DSAA: Dual-Stage Attribute Activation for Fine-grained Open Vocabulary Detection
May 18, 2026Donghong Jiang, Endian Lin, Hanqing Liu +4Open-Vocabulary Object Detection Fine-Grained Visual Perception
Beijing University of Posts and Telecommunications · Beijing E-Hualu Information Technology Co., Ltd. · State Key Laboratory of General Artificial Intelligence, BIGAI, Beijing, China
See What I Mean: Aligning Vision and Language Representations for Video Fine-grained Object Understanding
May 18, 2026Boyuan Sun, Bowen Yin, Yuanming Li +2Cross-Modal Learning Video Object Segmentation
VCIP, CS, Nankai University · Tongyi Lab, Alibaba Group · NKIARI, Shenzhen Futian
EPIC-Bench: A Perception-Centric Benchmark for Fine-Grained Embodied Visual Grounding in Vision-Language Models
May 16, 2026Haozhe Shan, Xiancong Ren, Han Dong +9VLM Evaluation Vision-Language Grounding
X-Humanoid · University of New South Wales · University of Science and Technology of China +4
How to Choose Your Teacher for Fine Grained Image Recognition
May 15, 2026Oswin Gosal, Edwin Arkel Rios, Augusto Christian Surya +3Fine-Grained Image Classification Teacher-Student Learning
National Tsing Hua University, Taiwan · National Yang Ming Chiao Tung University, Taiwan
From Scenes to Elements: Multi-Granularity Evidence Retrieval for Verifiable Multimodal RAG
May 14, 2026Guanhua Chen, Chuyue Huang, Yutong Yao +4Multimodal RAG Multimodal Grounding
NLP2CT Lab, Department of Computer and Information Science, University of Macau
SceneParser: Hierarchical Scene Parsing for Visual Semantics Understanding
May 14, 2026Pengxin Xu, Xincheng Lin, Luping Xiao +5Fine-Grained Visual Perception Multimodal Understanding
Harbin Institute of Technology, Shenzhen · Zhongguancun Academy · Huazhong University of Science and Technology +4
FIKA-Bench: From Fine-grained Recognition to Fine-Grained Knowledge Acquisition
May 13, 2026Geng Li, Yuxin PengVLM Evaluation Fine-Grained Visual Perception
1Wangxuan Institute of Computer Technology, Peking University, China
UHR-Micro: Diagnosing and Mitigating the Resolution Illusion in Earth Observation VLMs
May 12, 2026Shuo Ni, Tong Wang, Jing Zhang +5VLM Evaluation Remote Sensing Image Understanding
National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing, Beijing Institute of Technology, Beijing, China · Zhongguancun Academy, Beijing, China · School of Computer Science, Wuhan University, Wuhan, China +2
Count Anything at Any Granularity
May 11, 2026Chang Liu, Haoning Wu, Weidi XieObject Counting Multimodal Large Language Models
School of Artificial Intelligence, Shanghai Jiao Tong University, China · CMIC, Shanghai Jiao Tong University, China
Explainable Part-Based Vehicle Classifier with Spatial Awareness
May 8, 2026Andreas Caduff, Klaus Zahn, Jonas Hofstetter +2Intelligent Transportation Systems Explainable Image Classification
Competence Center for Intelligent Sensors and Networks, Lucerne University of Applied Science and Art · Competence Center for Intelligent Sensors and Networks, Lucerne University of Applied Science and Art, Technikumstr. 21, Horw, 6048, Switzerland. · SICK AG +1
ShellfishNet: A Domain-Specific Benchmark for Visual Recognition of Marine Molluscs
May 8, 2026Ziheng Zhou, Yang Wang, Nan Wang +2Image Retrieval Fine-Grained Visual Perception
IT College, Shanghai Ocean University · Fudan University · DP Technology
Fine-tuning a vision-language model for fracture-surface morphology recognition
May 8, 2026Quanliang Liu, Jungtaek Kim, Kangwook Lee +1VLM Adaptation Materials Science
Department of Materials Science & Engineering, University of Wisconsin–Madison, Madison, WI, USA, 53706 · Department of Electrical & Computer Engineering, University of Wisconsin–Madison, Madison, WI, USA, 53706 · KRAFTON, Gangnam-gu, Seoul, Republic of Korea, 06142 +1

Jun 2, 2026, cs.CVJ/K move · Enter open · S save

P $^2$ -DPO: Grounding Hallucination in Perceptual Processing via Calibration Direct Preference Optimization

Ruipeng Zhang, Zhihao Li, Haozhang Yuan, C. L. Philip Chen+1

Guangdong Provincial Key Laboratory of Computational AI Models and Cognitive Intelligence, School of Computer Science & Engineering, South China University of Technology · Pazhou Lab, Guangzhou, China · Engineering Research Center of the Ministry of Education on Health Intelligent Perception and Paralleled Digital-Human, Guangzhou, China

VLM Robustness Direct Preference Optimization Object Hallucination in VLMs Fine-Grained Visual Perception VLM Hallucination Mitigation

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Hallucination has recently garnered significant research attention in Large Vision-Language Models (LVLMs). Direct Preference Optimization (DPO) aims to learn directly from the corrected preferences provided by humans, thereby addressing the hallucination issue. Despite its success, this paradigm has yet to specifically target the perceptual bottleneck in attended regions or address insufficient Visual Robustness against image degradation. Furthermore, existing preference pairs are often vision-agnostic and their inherently off-policy nature limits their effectiveness in guiding model learning. To address these challenges, we propose Perceptual Processing Direct Preference Optimization (P

^2

-DPO), a novel training paradigm in which the model generates and learns from its own preference pairs, thereby directly addressing the identified visual bottlenecks while inherently avoiding the issues of vision-agnostic and off-policy data. It introduces: (1) an on-policy preference pairs construction method targeting Focus-and-Enhance perception and Visual Robustness, and (2) a well-designed Calibration Loss to precisely align visual signals with the causal generation of text. Experimental results demonstrate that with a comparable amount of training data and cost, P

^2

-DPO outperforms strong baselines that rely on costly human feedback on benchmarks. Furthermore, evaluations on Attention Region Fidelity (ARF) and image degradation scenarios validate the effectiveness of P

^2

-DPO in addressing perceptual bottleneck in attended regions and improving Visual Robustness against degraded inputs.

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