10 papers
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…
ESearch-R1: Learning Cost-Aware MLLM Agents for Interactive Embodied Search via Reinforcement Learning
Weijie Zhou, Xuangtang Xiong, Ye Tian +8
Multimodal Large Language Models (MLLMs) have empowered embodied agents with remarkable capabilities in planning and reasoning. However, when facing ambiguous natural language inst…
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…
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…
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…
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…