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20232026
most citedReuse and Diffuse: Iterative Denoising for Text-to-Video Generation

9 citations · 9 across the 5 of their papers we have counts for

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cs.CV2026

Dual-Path Hyperprior Informed Deep Unfolding Network for Image Compressive Sensing

Tianyi Lu, Wenxue Cui, Shaohui Liu

Recent Deep Unfolding Networks (DUNs) have significantly advanced Compressive Sensing (CS) by integrating iterative optimization with deep networks. However, existing DUNs still su…

cs.CV2024

Zero-shot High-fidelity and Pose-controllable Character Animation

Bingwen Zhu, Fanyi Wang, Tianyi Lu +7

Image-to-video (I2V) generation aims to create a video sequence from a single image, which requires high temporal coherence and visual fidelity. However, existing approaches suffer…

cs.CV2023

MagDiff: Multi-Alignment Diffusion for High-Fidelity Video Generation and Editing

Haoyu Zhao, Tianyi Lu, Jiaxi Gu +5

The diffusion model is widely leveraged for either video generation or video editing. As each field has its task-specific problems, it is difficult to merely develop a single diffu…

cs.CV2023

Fuse Your Latents: Video Editing with Multi-source Latent Diffusion Models

Tianyi Lu, Xing Zhang, Jiaxi Gu +5

Latent Diffusion Models (LDMs) are renowned for their powerful capabilities in image and video synthesis. Yet, compared to text-to-image (T2I) editing, text-to-video (T2V) editing…

cs.CV20239 cited

Reuse and Diffuse: Iterative Denoising for Text-to-Video Generation

Jiaxi Gu, Shicong Wang, Haoyu Zhao +7

Inspired by the remarkable success of Latent Diffusion Models (LDMs) for image synthesis, we study LDM for text-to-video generation, which is a formidable challenge due to the comp…