147 citations · 283 across the 36 of their papers we have counts for
7 papers · 1 filter
Omni-Referring Image Segmentation
Qiancheng Zheng, Yunhang Shen, Gen Luo +5
In this paper, we propose a novel task termed Omni-Referring Image Segmentation (OmniRIS) towards highly generalized image segmentation. Compared with existing unimodally condition…
FlexiReID: Adaptive Mixture of Expert for Multi-Modal Person Re-Identification
Zhen Sun, Lei Tan, Yunhang Shen +5
Multimodal person re-identification (Re-ID) aims to match pedestrian images across different modalities. However, most existing methods focus on limited cross-modal settings and fa…
Zooming from Context to Cue: Hierarchical Preference Optimization for Multi-Image MLLMs
Xudong Li, Mengdan Zhang, Peixian Chen +8
Multi-modal Large Language Models (MLLMs) excel at single-image tasks but struggle with multi-image understanding due to cross-modal misalignment, leading to hallucinations (contex…
What You Perceive Is What You Conceive: A Cognition-Inspired Framework for Open Vocabulary Image Segmentation
Jianghang Lin, Yue Hu, Jiangtao Shen +4
Open vocabulary image segmentation tackles the challenge of recognizing dynamically adjustable, predefined novel categories at inference time by leveraging vision-language alignmen…
Pseudo-Label Quality Decoupling and Correction for Semi-Supervised Instance Segmentation
Jianghang Lin, Yilin Lu, Yunhang Shen +4
Semi-Supervised Instance Segmentation (SSIS) involves classifying and grouping image pixels into distinct object instances using limited labeled data. This learning paradigm usuall…
From Objects to Events: Unlocking Complex Visual Understanding in Object Detectors via LLM-guided Symbolic Reasoning
Yuhui Zeng, Haoxiang Wu, Wenjie Nie +6
Current object detectors excel at entity localization and classification, yet exhibit inherent limitations in event recognition capabilities. This deficiency arises from their arch…
Long-VITA: Scaling Large Multi-modal Models to 1 Million Tokens with Leading Short-Context Accuracy
Yunhang Shen, Chaoyou Fu, Shaoqi Dong +14
We introduce Long-VITA, a simple yet effective large multi-modal model for long-context visual-language understanding tasks. It is adept at concurrently processing and analyzing mo…