4 citations · 7 across the 15 of their papers we have counts for
15 papers · 1 filter
ABot-M0.5: Unified Mobility-and-Manipulation World Action Model
Ronghan Chen, Yandan Yang, Zuojin Tang +18
Mobile manipulation is a key capability for general-purpose robots, yet remains challenging for current embodied learning methods. VLA policies are typically reactive and lack expl…
PhysEditWorld: A Large-Scale Dataset Toward Physics-Editable World Models
Bin Hu, Yanwen Ma, Jiehui Huang +14
Recent game world models can synthesize visually plausible, action-conditioned rollouts. However, their interaction behaviors often remain limited to exploratory or wandering traje…
Count Anything at Any Granularity
Chang Liu, Haoning Wu, Weidi Xie
Open-world object counting remains brittle: despite rapid advances in vision-language models (VLMs), reliably counting the objects a user intends is far from solved. We argue that…
Improving Human Image Animation via Semantic Representation Alignment
Chang Liu, Mengting Chen, Yixuan Huang +5
The field of image-to-video generation has made remarkable progress. However, challenges such as human limb twisting and facial distortion persist, especially when generating long…
OmniStream: Mastering Perception, Reconstruction and Action in Continuous Streams
Yibin Yan, Jilan Xu, Shangzhe Di +2
Modern visual agents require representations that are general, causal, and physically structured to operate in real-time streaming environments. However, current vision foundation…
SoccerMaster: A Vision Foundation Model for Soccer Understanding
Haolin Yang, Jiayuan Rao, Haoning Wu +1
Soccer understanding has recently garnered growing research interest due to its domain-specific complexity and unique challenges. Unlike prior works that typically rely on isolated…
SceneGen: Single-Image 3D Scene Generation in One Feedforward Pass
Yanxu Meng, Haoning Wu, Ya Zhang +1
3D content generation has recently attracted significant research interest, driven by its critical applications in VR/AR and embodied AI. In this work, we tackle the challenging ta…
SpatialScore: Towards Comprehensive Evaluation for Spatial Intelligence
Haoning Wu, Xiao Huang, Yaohui Chen +3
Existing evaluations of multimodal large language models (MLLMs) on spatial intelligence are typically fragmented and limited in scope. In this work, we aim to conduct a holistic a…
Multi-Agent System for Comprehensive Soccer Understanding
Jiayuan Rao, Zifeng Li, Haoning Wu +3
Recent advances in soccer understanding have demonstrated rapid progress, yet existing research predominantly focuses on isolated or narrow tasks. To bridge this gap, we propose a…
MRGen: Segmentation Data Engine for Underrepresented MRI Modalities
Haoning Wu, Ziheng Zhao, Ya Zhang +2
Training medical image segmentation models for rare yet clinically important imaging modalities is challenging due to the scarcity of annotated data, and manual mask annotations ca…
Towards Universal Soccer Video Understanding
Jiayuan Rao, Haoning Wu, Hao Jiang +3
As a globally celebrated sport, soccer has attracted widespread interest from fans all over the world. This paper aims to develop a comprehensive multi-modal framework for soccer v…
MegaFusion: Extend Diffusion Models towards Higher-resolution Image Generation without Further Tuning
Haoning Wu, Shaocheng Shen, Qiang Hu +3
Diffusion models have emerged as frontrunners in text-to-image generation, but their fixed image resolution during training often leads to challenges in high-resolution image gener…
MatchTime: Towards Automatic Soccer Game Commentary Generation
Jiayuan Rao, Haoning Wu, Chang Liu +2
Soccer is a globally popular sport with a vast audience, in this paper, we consider constructing an automatic soccer game commentary model to improve the audiences' viewing experie…
Boost Video Frame Interpolation via Motion Adaptation
Haoning Wu, Xiaoyun Zhang, Weidi Xie +2
Video frame interpolation (VFI) is a challenging task that aims to generate intermediate frames between two consecutive frames in a video. Existing learning-based VFI methods have…
Intelligent Grimm -- Open-ended Visual Storytelling via Latent Diffusion Models
Chang Liu, Haoning Wu, Yujie Zhong +3
Generative models have recently exhibited exceptional capabilities in text-to-image generation, but still struggle to generate image sequences coherently. In this work, we focus on…