14 papers
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…
Scaling Mixture-of-Experts Video Pretraining for Embodied Intelligence
Shuailei Ma, Jiaqi Liao, Xinyang Wang +24
Despite the recent promise in robot control, video generative models suffer from a domain mismatch due to their primary focus on content creation. For example, their design inheren…
WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation
Yuwei Niu, Munan Ning, Mengren Zheng +9
Text-to-Image (T2I) models are capable of generating high-quality artistic creations and visual content. However, existing research and evaluation standards predominantly focus on…
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…
Enhancing Spatial Understanding in Image Generation via Reward Modeling
Zhenyu Tang, Chaoran Feng, Yufan Deng +5
Recent progress in text-to-image generation has greatly advanced visual fidelity and creativity, but it has also imposed higher demands on prompt complexity-particularly in encodin…
Tune-Your-Style: Intensity-tunable 3D Style Transfer with Gaussian Splatting
Yian Zhao, Rushi Ye, Ruochong Zheng +6
3D style transfer refers to the artistic stylization of 3D assets based on reference style images. Recently, 3DGS-based stylization methods have drawn considerable attention, prima…