activity
20232026
most citedViewCrafter: Taming Video Diffusion Models for High-fidelity Novel View Synthesis

3 citations · 11 across the 19 of their papers we have counts for

collaborators

21 papers

cs.CV2026

Multics: Generative Multi-Player World Model with Hierarchical Communication

Kaiyi Huang, Wangbo Yu, Yukun Huang +6

Multi-player interactive world models aim to simulate shared environments from multiple players' perspectives, but achieving robust generation while scaling to more players remains…

cs.CV2026

GameHorizon Suite: Multi-Horizon Data and Evaluation in Gameplay

Yiran Wang, Xingyilang Yin, Junfu Pu +12

Modern video games provide a measurable testbed for AI models, combining abilities of visual understanding, instruction decomposition, goal planning, and precise action control ove…

cs.CV2026

WorldCrafter: Consistent Video World Model with Implicit 3D-aware Memory

Wangbo Yu, Kunhao Liu, Wenbo Hu +8

Video world models enable interactive exploration of dynamic environments, yet struggle to respect prior observations over long horizons and across viewpoints. We present WorldCraf…

cs.CV2026

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models

Haiyang Zhou, Wangbo Yu, Chaoran Feng +3

The abundance of casually captured monocular videos and images on social media provides a valuable source for immersive content creation, where generating novel views from such spa…

cs.CV2026

DeblurNVS: Geometric Latent Diffusion for Novel View Synthesis from Sparse Motion-Blurred Images

Changyue Shi, Wangbo Yu, Chaoran Feng +1

Novel view synthesis (NVS) is a fundamental problem in computer vision and graphics. Recent advances in neural radiance fields (NeRF), 3D Gaussian Splatting (3DGS), and generative…

cs.CV2025

Breaking the Vicious Cycle: Coherent 3D Gaussian Splatting from Sparse and Motion-Blurred Views

Zhankuo Xu, Chaoran Feng, Yingtao Li +5

3D Gaussian Splatting (3DGS) has emerged as a state-of-the-art method for novel view synthesis. However, its performance heavily relies on dense, high-quality input imagery, an ass…

cs.CV2025

Uniworld-V2: Reinforce Image Editing with Diffusion Negative-aware Finetuning and MLLM Implicit Feedback

Zongjian Li, Zheyuan Liu, Qihui Zhang +10

Instruction-based image editing has achieved remarkable progress; however, models solely trained via supervised fine-tuning often overfit to annotated patterns, hindering their abi…

cs.CV2025

E-4DGS: High-Fidelity Dynamic Reconstruction from the Multi-view Event Cameras

Chaoran Feng, Zhenyu Tang, Wangbo Yu +5

Novel view synthesis and 4D reconstruction techniques predominantly rely on RGB cameras, thereby inheriting inherent limitations such as the dependence on adequate lighting, suscep…

cs.CV2025

UniWorld-V1: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation

Bin Lin, Zongjian Li, Xinhua Cheng +9

Although existing unified models achieve strong performance in vision-language understanding and text-to-image generation, they remain limited in addressing image perception and ma…

cs.CV2025

GS2E: Gaussian Splatting is an Effective Data Generator for Event Stream Generation

Yuchen Li, Chaoran Feng, Zhenyu Tang +4

We introduce GS2E (Gaussian Splatting to Event), a large-scale synthetic event dataset for high-fidelity event vision tasks, captured from real-world sparse multi-view RGB images.…

cs.CV2025

HoloTime: Taming Video Diffusion Models for Panoramic 4D Scene Generation

Haiyang Zhou, Wangbo Yu, Jiawen Guan +3

The rapid advancement of diffusion models holds the promise of revolutionizing the application of VR and AR technologies, which typically require scene-level 4D assets for user exp…

cs.CV2025

NeuralGS: Bridging Neural Fields and 3D Gaussian Splatting for Compact 3D Representations

Zhenyu Tang, Chaoran Feng, Xinhua Cheng +6

3D Gaussian Splatting (3DGS) achieves impressive quality and rendering speed, but with millions of 3D Gaussians and significant storage and transmission costs. In this paper, we ai…

cs.CV2025

Video SimpleQA: Towards Factuality Evaluation in Large Video Language Models

Meng Cao, Pengfei Hu, Yingyao Wang +12

Recent advancements in Large Video Language Models (LVLMs) have highlighted their potential for multi-modal understanding, yet evaluating their factual grounding in videos remains…

cs.CV2025★ 1 cited

AE-NeRF: Augmenting Event-Based Neural Radiance Fields for Non-ideal Conditions and Larger Scene

Chaoran Feng, Wangbo Yu, Xinhua Cheng +4

Compared to frame-based methods, computational neuromorphic imaging using event cameras offers significant advantages, such as minimal motion blur, enhanced temporal resolution, an…

cs.CV2024

RoomPainter: View-Integrated Diffusion for Consistent Indoor Scene Texturing

Zhipeng Huang, Wangbo Yu, Xinhua Cheng +5

Indoor scene texture synthesis has garnered significant interest due to its important potential applications in virtual reality, digital media and creative arts. Existing diffusion…

cs.CV2024★ 3 cited

ViewCrafter: Taming Video Diffusion Models for High-fidelity Novel View Synthesis

Wangbo Yu, Jinbo Xing, Li Yuan +7

Despite recent advancements in neural 3D reconstruction, the dependence on dense multi-view captures restricts their broader applicability. In this work, we propose \textbf{ViewCra…

cs.CV2024★ 1 cited

Cycle3D: High-quality and Consistent Image-to-3D Generation via Generation-Reconstruction Cycle

Zhenyu Tang, Junwu Zhang, Xinhua Cheng +5

Recent 3D large reconstruction models typically employ a two-stage process, including first generate multi-view images by a multi-view diffusion model, and then utilize a feed-forw…

cs.CV2024★ 2 cited

HoloDreamer: Holistic 3D Panoramic World Generation from Text Descriptions

Haiyang Zhou, Xinhua Cheng, Wangbo Yu +2

3D scene generation is in high demand across various domains, including virtual reality, gaming, and the film industry. Owing to the powerful generative capabilities of text-to-ima…

cs.CV2024★ 3 cited

EvaGaussians: Event Stream Assisted Gaussian Splatting from Blurry Images

Wangbo Yu, Chaoran Feng, Jiye Tang +6

3D Gaussian Splatting (3D-GS) has demonstrated exceptional capabilities in 3D scene reconstruction and novel view synthesis. However, its training heavily depends on high-quality,…

cs.CV2023

Repaint123: Fast and High-quality One Image to 3D Generation with Progressive Controllable 2D Repainting

Junwu Zhang, Zhenyu Tang, Yatian Pang +5

Recent one image to 3D generation methods commonly adopt Score Distillation Sampling (SDS). Despite the impressive results, there are multiple deficiencies including multi-view inc…

cs.CV2023★ 1 cited

HiFi-123: Towards High-fidelity One Image to 3D Content Generation

Wangbo Yu, Li Yuan, Yan-Pei Cao +6

Recent advances in diffusion models have enabled 3D generation from a single image. However, current methods often produce suboptimal results for novel views, with blurred textures…