5 papers
LabInstruct: Benchmarking Situated Instructional Video Generation for Lab Procedures
Yuming Fu, Weijia Wu, Jing Chen +5
Self-driving laboratories (SDLs) aim to automate the full experimental loop, from scientific decision-making to physical execution. Ideally, AI-generated plans could be carried out…
Dream.exe: Can Video Generation Models Dream Executable Robot Manipulation?
Rui Zhao, Kaiming Yang, Jifeng Zhu +6
Video generation models have made impressive strides in synthesizing visually compelling content, yet their outputs remain confined to the virtual domain. A natural question follow…
MIND: Benchmarking Memory Consistency and Action Control in World Models
Yixuan Ye, Xuanyu Lu, Yuxin Jiang +7
World models aim to understand, remember, and predict dynamic visual environments, yet a unified benchmark for evaluating their fundamental abilities remains lacking. To address th…
VideoASMR-Bench: Can AI-Generated ASMR Videos Fool VLMs and Humans?
Jiaqi Wang, Weijia Wu, Yi Zhan +6
With AI-generated videos increasingly indistinguishable from reality, current benchmarks primarily focus on broad semantic alignment and basic physical consistency, offering limite…
DragAnything: Motion Control for Anything using Entity Representation
Weijia Wu, Zhuang Li, Yuchao Gu +7
We introduce DragAnything, which utilizes a entity representation to achieve motion control for any object in controllable video generation. Comparison to existing motion control m…