1 citations · 1 across the 13 of their papers we have counts for
14 papers
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…
LongLive-2.0: An NVFP4 Parallel Infrastructure for Long Video Generation
Yukang Chen, Luozhou Wang, Wei Huang +13
We present LongLive-2.0, an NVFP4-based parallel infrastructure throughout the full training and inference workflow of long video generation, addressing speed and memory bottleneck…
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…
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…
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…
4D Driving Scene Generation With Stereo Forcing
Hao Lu, Zhuang Ma, Guangfeng Jiang +6
Current generative models struggle to synthesize dynamic 4D driving scenes that simultaneously support temporal extrapolation and spatial novel view synthesis (NVS) without per-sce…
SDPose: Exploiting Diffusion Priors for Out-of-Domain and Robust Pose Estimation
Shuang Liang, Jing He, Chuanmeizhi Wang +4
Pre-trained diffusion models provide rich latent features across U-Net levels and are emerging as powerful vision backbones. While prior works such as Marigold and Lotus repurpose…
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…
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 (…
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…
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…
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,…
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…
Towards Faster Training of Diffusion Models: An Inspiration of A Consistency Phenomenon
Tianshuo Xu, Peng Mi, Ruilin Wang +1
Diffusion models (DMs) are a powerful generative framework that have attracted significant attention in recent years. However, the high computational cost of training DMs limits th…