1 citations · 1 across the 9 of their papers we have counts for
11 papers
VDOT++: Unified Few-Step Video Generation via Unbalanced Optimal Transport Distillation
Yutong Wang, Xingtong Ge, Enhuai Liu +6
Video creation spans text-to-video (T2V), image-to-video (I2V), and condition-based generation, yet video diffusion models remain costly because they repeatedly evaluate large back…
PulseQuant: Propagation-Guided Subspace Correction for 4-Bit Video Diffusion Transformers
Yutong Wang, Xingtong Ge, Enhuai Liu +4
Quantization errors in video diffusion transformers can be amplified or attenuated by subsequent denoising updates, making local reconstruction error an incomplete predictor of fin…
RealVDeblur: One-Step Diffusion for Generalizable Real-World Video Deblurring
Renbiao Jin, Mingxin Yang, Yutian Chen +8
Real-world video deblurring remains challenging due to diverse motion patterns, complex degradations, and the scarcity of realistic training data, yet robust restoration is critica…
PARE: Pruning and Adaptive Routing for Efficient Video Generation
Yutong Wang, Yunke Wang, Tianfan Xue +4
Video Diffusion Transformers (DiTs) generate high-quality videos but demand substantial compute due to wide blocks, deep architectures, and iterative sampling. Recent methods reduc…
AsyncEvGS: Asynchronous Event-Assisted Gaussian Splatting for Handheld Motion-Blurred Scenes
Jun Dai, Renbiao Jin, Bo Xu +5
3D reconstruction methods such as 3D Gaussian Splatting (3DGS) and Neural Radiance Fields (NeRF) achieve impressive photorealism but fail when input images suffer from severe motio…
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…