9 citations · 34 across the 44 of their papers we have counts for
20 papers · 1 filter
Yo'City: Personalized and Boundless 3D Realistic City Scene Generation via Self-Critic Expansion
Keyang Lu, Sifan Zhou, Hongbin Xu +6
Realistic 3D city generation is fundamental to a wide range of applications, including virtual reality and digital twins. However, most existing methods rely on training a single d…
NeAR: Coupled Neural Asset-Renderer Stack
Hong Li, Chongjie Ye, Houyuan Chen +12
Neural asset authoring and neural rendering have traditionally evolved as disjoint paradigms: one generates digital assets for fixed graphics pipelines, while the other maps conven…
Thinking with Camera: A Unified Multimodal Model for Camera-Centric Understanding and Generation
Kang Liao, Size Wu, Zhonghua Wu +6
Camera-centric understanding and generation are two cornerstones of spatial intelligence, yet they are typically studied in isolation. We present Puffin, a unified camera-centric m…
PanoWorld-X: Generating Explorable Panoramic Worlds via Sphere-Aware Video Diffusion
Yuyang Yin, HaoXiang Guo, Fangfu Liu +7
Generating a complete and explorable 360-degree visual world enables a wide range of downstream applications. While prior works have advanced the field, they remain constrained by…
BranchGRPO: Stable and Efficient GRPO with Structured Branching in Diffusion Models
Yuming Li, Yikai Wang, Yuying Zhu +4
Recent progress in aligning image and video generative models with Group Relative Policy Optimization (GRPO) has improved human preference alignment, but existing variants remain i…
MotionFlow:Learning Implicit Motion Flow for Complex Camera Trajectory Control in Video Generation
Guojun Lei, Chi Wang, Yikai Wang +3
Generating videos guided by camera trajectories poses significant challenges in achieving consistency and generalizability, particularly when both camera and object motions are pre…
PanoLora: Bridging Perspective and Panoramic Video Generation with LoRA Adaptation
Zeyu Dong, Yuyang Yin, Yuqi Li +3
Generating high-quality 360° panoramic videos remains a significant challenge due to the fundamental differences between panoramic and traditional perspective-view projections. Whi…
EGTM: Event-guided Efficient Turbulence Mitigation
Huanan Li, Rui Fan, Juntao Guan +5
Turbulence mitigation (TM) aims to remove the stochastic distortions and blurs introduced by atmospheric turbulence into frame cameras. Existing state-of-the-art deep-learning TM m…
Matrix-3D: Omnidirectional Explorable 3D World Generation
Zhongqi Yang, Wenhang Ge, Yuqi Li +12
Explorable 3D world generation from a single image or text prompt forms a cornerstone of spatial intelligence. Recent works utilize video model to achieve wide-scope and generaliza…
Next Visual Granularity Generation
Yikai Wang, Zhouxia Wang, Zhonghua Wu +3
We propose a novel approach to image generation by decomposing an image into a structured sequence, where each element in the sequence shares the same spatial resolution but differ…
Ultra3D: Efficient and High-Fidelity 3D Generation with Part Attention
Yiwen Chen, Zhihao Li, Yikai Wang +4
Recent advances in sparse voxel representations have significantly improved the quality of 3D content generation, enabling high-resolution modeling with fine-grained geometry. Howe…
Light of Normals: Unified Feature Representation for Universal Photometric Stereo
Houyuan Chen, Hong Li, Chongjie Ye +11
Universal photometric stereo (PS) is defined by two factors: it must (i) operate under arbitrary, unknown lighting conditions and (ii) avoid reliance on specific illumination model…
FlowDreamer: A RGB-D World Model with Flow-based Motion Representations for Robot Manipulation
Jun Guo, Xiaojian Ma, Yikai Wang +3
This paper investigates training better visual world models for robot manipulation, i.e., models that can predict future visual observations by conditioning on past frames and robo…
MeshGen: Generating PBR Textured Mesh with Render-Enhanced Auto-Encoder and Generative Data Augmentation
Zilong Chen, Yikai Wang, Wenqiang Sun +3
In this paper, we introduce MeshGen, an advanced image-to-3D pipeline that generates high-quality 3D meshes with detailed geometry and physically based rendering (PBR) textures. Ad…
Video4DGen: Enhancing Video and 4D Generation through Mutual Optimization
Yikai Wang, Guangce Liu, Xinzhou Wang +5
The advancement of 4D (i.e., sequential 3D) generation opens up new possibilities for lifelike experiences in various applications, where users can explore dynamic objects or chara…
FB-4D: Spatial-Temporal Coherent Dynamic 3D Content Generation with Feature Banks
Jinwei Li, Huan-ang Gao, Wenyi Li +13
With the rapid advancements in diffusion models and 3D generation techniques, dynamic 3D content generation has become a crucial research area. However, achieving high-fidelity 4D…
DeepMesh: Auto-Regressive Artist-mesh Creation with Reinforcement Learning
Ruowen Zhao, Junliang Ye, Zhengyi Wang +4
Triangle meshes play a crucial role in 3D applications for efficient manipulation and rendering. While auto-regressive methods generate structured meshes by predicting discrete ver…
FlexWorld: Progressively Expanding 3D Scenes for Flexiable-View Synthesis
Luxi Chen, Zihan Zhou, Min Zhao +6
Generating flexible-view 3D scenes, including 360° rotation and zooming, from single images is challenging due to a lack of 3D data. To this end, we introduce FlexWorld, a novel fr…
AR-1-to-3: Single Image to Consistent 3D Object Generation via Next-View Prediction
Xuying Zhang, Yupeng Zhou, Kai Wang +6
Novel view synthesis (NVS) is a cornerstone for image-to-3d creation. However, existing works still struggle to maintain consistency between the generated views and the input views…
Advanced representation learning for flow field analysis and reconstruction
Yikai Wang, Jiameng Wang, Ruyi Han +1
In this paper we present advanced representation learning study on integrating deep learning techniques and sparse approximation, including diffusion models, for advanced flow fiel…