1 citations · 1 across the 6 of their papers we have counts for
6 papers
AnyRecon: Arbitrary-View 3D Reconstruction with Video Diffusion Model
Yutian Chen, Shi Guo, Renbiao Jin +7
Sparse-view 3D reconstruction is essential for modeling scenes from casual captures, but remain challenging for non-generative reconstruction. Existing diffusion-based approaches m…
Less Gaussians, Texture More: 4K Feed-Forward Textured Splatting
Yixing Lao, Xuyang Bai, Xiaoyang Wu +7
Existing feed-forward 3D Gaussian Splatting methods predict pixel-aligned primitives, leading to a quadratic growth in primitive count as resolution increases. This fundamentally l…
CamCloneMaster: Enabling Reference-based Camera Control for Video Generation
Yawen Luo, Jianhong Bai, Xiaoyu Shi +6
Camera control is crucial for generating expressive and cinematic videos. Existing methods rely on explicit sequences of camera parameters as control conditions, which can be cumbe…
EvMic: Event-based Non-contact sound recovery from effective spatial-temporal modeling
Hao Yin, Shi Guo, Xu Jia +6
When sound waves hit an object, they induce vibrations that produce high-frequency and subtle visual changes, which can be used for recovering the sound. Early studies always encou…
CineMaster: A 3D-Aware and Controllable Framework for Cinematic Text-to-Video Generation
Qinghe Wang, Yawen Luo, Xiaoyu Shi +7
In this work, we present CineMaster, a novel framework for 3D-aware and controllable text-to-video generation. Our goal is to empower users with comparable controllability as profe…
Consistent Diffusion: Denoising Diffusion Model with Data-Consistent Training for Image Restoration
Xinlong Cheng, Tiantian Cao, Guoan Cheng +7
In this work, we address the limitations of denoising diffusion models (DDMs) in image restoration tasks, particularly the shape and color distortions that can compromise image qua…