11 papers
MotionEnhancer: Leveraging Video Diffusion for Motion-Enhanced Vision-Language Models
Yifan Xu, Chao Zhang, Ruifei Ma +4
The new era has witnessed a remarkable capability to extend Vision-Language Models (VLMs) for tackling tasks of video understanding. While current VLMs excel at event- or story-lev…
FlowScene: Style-Consistent Indoor Scene Generation with Multimodal Graph Rectified Flow
Zhifei Yang, Guangyao Zhai, Keyang Lu +6
Scene generation has extensive industrial applications, demanding both high realism and precise control over geometry and appearance. Language-driven retrieval methods compose plau…
Yo'City: Personalized and Boundless 3D Realistic City Scene Generation via Self-Critic Expansion
Keyang Lu, Sifan Zhou, Hongbin Xu +6
Realistic 3D city generation is fundamental to a wide range of applications, including virtual reality and digital twins. However, most existing methods rely on training a single d…
Gradient as Conditions: Rethinking HOG for All-in-one Image Restoration
Jiawei Wu, Zhifei Yang, Zhe Wang +1
All-in-one image restoration (AIR) aims to address diverse degradations within a unified model by leveraging informative degradation conditions to guide the restoration process. Ho…
VidText: Towards Comprehensive Evaluation for Video Text Understanding
Zhoufaran Yang, Yan Shu, Jing Wang +8
Visual texts embedded in videos carry rich semantic information, which is crucial for both holistic video understanding and fine-grained reasoning about local human actions. Howeve…
Spatial 3D-LLM: Exploring Spatial Awareness in 3D Vision-Language Models
Xiaoyan Wang, Zeju Li, Yifan Xu +5
New era has unlocked exciting possibilities for extending Large Language Models (LLMs) to tackle 3D vision-language tasks. However, most existing 3D multimodal LLMs (MLLMs) rely on…