activity
20242026
most citedA Mechanistic View on Video Generation as World Models: State and Dynamics

1 citations · 1 across the 14 of their papers we have counts for

collaborators

15 papers

cs.AI2026

ReWorld: An Interactive World Model with Long-Horizon Memory

Zhifei Chen, Luozhou Wang, Guibao Shen +8

An interactive world model must follow the user's actions, remember the places it has shown, and stream in real time. The tension is structural: control wants a short horizon, memo…

cs.CV2026

RoboStressBench: Benchmarking VLM Robustness to Physical Visual Stress in Embodied Scenes

Leyi Wu, Yifan Zhao, Jinjie Zhang +11

Vision-Language Models (VLMs) have shown strong visual understanding and are increasingly deployed in embodied AI systems, where reliable perception under real conditions is essent…

cs.CV2026

LaMo: Self-Supervised Latent Motion Priors for Physical Realism in Video Generation

Bo Jiang, Depu Meng, Yihan Hu +3

Modern video generators produce visually compelling clips but still struggle with physical and motion consistency, limiting their use as reliable world simulators. Existing remedie…

cs.CV2026

Teaching Video Generators to Remember: Eliciting Dynamic Memory for Out-of-Sight State Evolution

Tianshuo Xu, Yichen Xie, Depu Meng +5

Video world models should maintain evolving states when evidence is unobserved, yet current generators often freeze hidden states upon interruption. This is not simply a capacity p…

cs.CV2026

SpectralSplat: Appearance-Disentangled Feed-Forward Gaussian Splatting for Driving Scenes

Quentin Herau, Tianshuo Xu, Depu Meng +5

Feed-forward 3D Gaussian Splatting methods have achieved impressive reconstruction quality for autonomous driving scenes, yet they entangle scene geometry with transient appearance…

cs.CV2026

Motion Forcing: A Decoupled Framework for Robust Video Generation in Motion Dynamics

Tianshuo Xu, Zhifei Chen, Leyi Wu +2

The ultimate goal of video generation is to satisfy a fundamental trilemma: achieving high visual quality, maintaining rigorous physical consistency, and enabling precise controlla…

cs.CV2026★ 1 cited

A Mechanistic View on Video Generation as World Models: State and Dynamics

Luozhou Wang, Zhifei Chen, Yihua Du +11

Large-scale video generation models have demonstrated emergent physical coherence, positioning them as potential world models. However, a gap remains between contemporary "stateles…

cs.CV2025

STANCE: Motion Coherent Video Generation Via Sparse-to-Dense Anchored Encoding

Zhifei Chen, Tianshuo Xu, Leyi Wu +6

Video generation has recently made striking visual progress, but maintaining coherent object motion and interactions remains difficult. We trace two practical bottlenecks: (i) huma…

cs.CV2025

UniCalli: A Unified Diffusion Framework for Column-Level Generation and Recognition of Chinese Calligraphy

Tianshuo Xu, Kai Wang, Zhifei Chen +4

Computational replication of Chinese calligraphy remains challenging. Existing methods falter, either creating high-quality isolated characters while ignoring page-level aesthetics…

cs.GR2025

FlexPainter: Flexible and Multi-View Consistent Texture Generation

Dongyu Yan, Leyi Wu, Jiantao Lin +7

Texture map production is an important part of 3D modeling and determines the rendering quality. Recently, diffusion-based methods have opened a new way for texture generation. How…

cs.RO2025

Occ-LLM: Enhancing Autonomous Driving with Occupancy-Based Large Language Models

Tianshuo Xu, Hao Lu, Xu Yan +3

Large Language Models (LLMs) have made substantial advancements in the field of robotic and autonomous driving. This study presents the first Occupancy-based Large Language Model (…

cs.CV2024

DrivingRecon: Large 4D Gaussian Reconstruction Model For Autonomous Driving

Hao Lu, Tianshuo Xu, Wenzhao Zheng +6

Photorealistic 4D reconstruction of street scenes is essential for developing real-world simulators in autonomous driving. However, most existing methods perform this task offline…

cs.CV2024

Uni-Renderer: Unifying Rendering and Inverse Rendering Via Dual Stream Diffusion

Zhifei Chen, Tianshuo Xu, Wenhang Ge +7

Rendering and inverse rendering are pivotal tasks in both computer vision and graphics. The rendering equation is the core of the two tasks, as an ideal conditional distribution tr…

cs.CV2024

Motion Dreamer: Boundary Conditional Motion Reasoning for Physically Coherent Video Generation

Tianshuo Xu, Zhifei Chen, Leyi Wu +5

Recent advances in video generation have shown promise for generating future scenarios, critical for planning and control in autonomous driving and embodied intelligence. However,…

cs.CV2024

From Bird's-Eye to Street View: Crafting Diverse and Condition-Aligned Images with Latent Diffusion Model

Xiaojie Xu, Tianshuo Xu, Fulong Ma +1

We explore Bird's-Eye View (BEV) generation, converting a BEV map into its corresponding multi-view street images. Valued for its unified spatial representation aiding multi-sensor…