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cs.CV2026

Listening with the Eyes: Benchmarking Egocentric Co-Speech Grounding across Space and Time

Weijie Zhou, Xuantang Xiong, Zhenlin Hu +6

In situated collaboration, speakers often use intentionally underspecified deictic commands (e.g., ``pass me \textit{that}''), whose referent becomes identifiable only by aligning…

cs.CV2026

GeM-VG: Towards Generalized Multi-image Visual Grounding with Multimodal Large Language Models

Shurong Zheng, Yousong Zhu, Hongyin Zhao +4

Multimodal Large Language Models (MLLMs) have demonstrated impressive progress in single-image grounding and general multi-image understanding. Recently, some methods begin to addr…

cs.CV2025

PhysVLM-AVR: Active Visual Reasoning for Multimodal Large Language Models in Physical Environments

Weijie Zhou, Xuantang Xiong, Yi Peng +5

Visual reasoning in multimodal large language models (MLLMs) has primarily been studied in static, fully observable settings, limiting their effectiveness in real-world environment…

cs.CV2025

FOCUS: Unified Vision-Language Modeling for Interactive Editing Driven by Referential Segmentation

Fan Yang, Yousong Zhu, Xin Li +6

Recent Large Vision Language Models (LVLMs) demonstrate promising capabilities in unifying visual understanding and generative modeling, enabling both accurate content understandin…

cs.CV2025

Referring Expression Instance Retrieval and A Strong End-to-End Baseline

Xiangzhao Hao, Kuan Zhu, Hongyu Guo +5

Using natural language to query visual information is a fundamental need in real-world applications. Text-Image Retrieval (TIR) retrieves a target image from a gallery based on an…

cs.CV2025

FOCUS: Fine-grained Optimization with Semantic Guided Understanding for Pedestrian Attributes Recognition

Hongyan An, Kuan Zhu, Xin He +4

Pedestrian attribute recognition (PAR) is a fundamental perception task in intelligent transportation and security. To tackle this fine-grained task, most existing methods focus on…