6 papers
Let ViT Speak: Generative Language-Image Pre-training
Yan Fang, Mengcheng Lan, Zilong Huang +7
In this paper, we present \textbf{Gen}erative \textbf{L}anguage-\textbf{I}mage \textbf{P}re-training (GenLIP), a minimalist generative pretraining framework for Vision Transformers…
CodeDance: A Dynamic Tool-integrated MLLM for Executable Visual Reasoning
Qi Song, Honglin Li, Yingchen Yu +6
Recent releases such as o3 highlight human-like "thinking with images" reasoning that combines tool use with stepwise verification, yet most open-source approaches still rely on te…
Monocular Normal Estimation via Shading Sequence Estimation
Zongrui Li, Xinhua Ma, Minghui Hu +6
Monocular normal estimation aims to estimate the normal map from a single RGB image of an object under arbitrary lights. Existing methods rely on deep models to directly predict no…
ThinkGen: Generalized Thinking for Visual Generation
Siyu Jiao, Yiheng Lin, Yujie Zhong +9
Recent progress in Multimodal Large Language Models (MLLMs) demonstrates that Chain-of-Thought (CoT) reasoning enables systematic solutions to complex understanding tasks. However,…
Text4Seg++: Advancing Image Segmentation via Generative Language Modeling
Mengcheng Lan, Chaofeng Chen, Jiaxing Xu +6
Multimodal Large Language Models (MLLMs) have shown exceptional capabilities in vision-language tasks. However, effectively integrating image segmentation into these models remains…
TimeExpert: An Expert-Guided Video LLM for Video Temporal Grounding
Zuhao Yang, Yingchen Yu, Yunqing Zhao +2
Video Temporal Grounding (VTG) aims to precisely identify video event segments in response to textual queries. The outputs of VTG tasks manifest as sequences of events, each define…