3 citations · 8 across the 22 of their papers we have counts for
22 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…
Can Large Language Models Execute Parent Orders?
Zane Shen, Xinli Xu, Guangyi Zhang +7
Parent-order execution is a core problem in algorithmic trading, where the goal is to split a large order into smaller orders while reducing execution costs. Existing approaches ei…
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…
PanoVGGT: Feed-Forward 3D Reconstruction from Panoramic Imagery
Yijing Guo, Mengjun Chao, Luo Wang +5
Panoramic imagery offers a full 360° field of view and is increasingly common in consumer devices. However, it introduces non-pinhole distortions that challenge joint pose estimati…
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…
CamPilot: Improving Camera Control in Video Diffusion Model with Efficient Camera Reward Feedback
Wenhang Ge, Guibao Shen, Jiawei Feng +5
Recent advances in camera-controlled video diffusion models have significantly improved video-camera alignment. However, the camera controllability still remains limited. In this w…
VideoMemory: Toward Consistent Video Generation via Memory Integration
Jinsong Zhou, Yihua Du, Xinli Xu +7
Maintaining consistent characters, props, and environments across multiple shots is a central challenge in narrative video generation. Existing models can produce high-quality shor…
StereoPilot: Learning Unified and Efficient Stereo Conversion via Generative Priors
Guibao Shen, Yihua Du, Wenhang Ge +7
The rapid growth of stereoscopic displays, including VR headsets and 3D cinemas, has led to increasing demand for high-quality stereo video content. However, producing 3D videos re…
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…
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…
ComfyMind: Toward General-Purpose Generation via Tree-Based Planning and Reactive Feedback
Litao Guo, Xinli Xu, Luozhou Wang +5
With the rapid advancement of generative models, general-purpose generation has gained increasing attention as a promising approach to unify diverse tasks across modalities within…
RectifiedHR: Enable Efficient High-Resolution Synthesis via Energy Rectification
Zhen Yang, Guibao Shen, Minyang Li +5
Diffusion models have achieved remarkable progress across various visual generation tasks. However, their performance significantly declines when generating content at resolutions…
TransPixeler: Advancing Text-to-Video Generation with Transparency
Luozhou Wang, Yijun Li, Zhifei Chen +5
Text-to-video generative models have made significant strides, enabling diverse applications in entertainment, advertising, and education. However, generating RGBA video, which inc…
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…
AerialGo: Walking-through City View Generation from Aerial Perspectives
Fuqiang Zhao, Yijing Guo, Siyuan Yang +6
High-quality 3D urban reconstruction is essential for applications in urban planning, navigation, and AR/VR. However, capturing detailed ground-level data across cities is both lab…
LucidFusion: Reconstructing 3D Gaussians with Arbitrary Unposed Images
Hao He, Yixun Liang, Luozhou Wang +5
Recent large reconstruction models have made notable progress in generating high-quality 3D objects from single images. However, current reconstruction methods often rely on explic…
SG-Adapter: Enhancing Text-to-Image Generation with Scene Graph Guidance
Guibao Shen, Luozhou Wang, Jiantao Lin +9
Recent advancements in text-to-image generation have been propelled by the development of diffusion models and multi-modality learning. However, since text is typically represented…
Motion Inversion for Video Customization
Luozhou Wang, Ziyang Mai, Guibao Shen +6
In this work, we present a novel approach for motion customization in video generation, addressing the widespread gap in the exploration of motion representation within video gener…
Denoising Diffusion Step-aware Models
Shuai Yang, Yukang Chen, Luozhou Wang +2
Denoising Diffusion Probabilistic Models (DDPMs) have garnered popularity for data generation across various domains. However, a significant bottleneck is the necessity for whole-n…
Not All Steps are Created Equal: Selective Diffusion Distillation for Image Manipulation
Luozhou Wang, Shuai Yang, Shu Liu +1
Conditional diffusion models have demonstrated impressive performance in image manipulation tasks. The general pipeline involves adding noise to the image and then denoising it. Ho…
Text-Anchored Score Composition: Tackling Condition Misalignment in Text-to-Image Diffusion Models
Luozhou Wang, Guibao Shen, Wenhang Ge +3
Text-to-image diffusion models have advanced towards more controllable generation via supporting various additional conditions (e.g.,depth map, bounding box) beyond text. However,…
Lift3D: Synthesize 3D Training Data by Lifting 2D GAN to 3D Generative Radiance Field
Leheng Li, Qing Lian, Luozhou Wang +2
This work explores the use of 3D generative models to synthesize training data for 3D vision tasks. The key requirements of the generative models are that the generated data should…