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

3 citations · 7 across the 12 of their papers we have counts for

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16 papers · 1 filter

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…