most citedVideoGigaGAN: Towards Detail-rich Video Super-Resolution

3 citations · 4 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2025

Diffusion Transformer-to-Mamba Distillation for High-Resolution Image Generation

Yuan Yao, Yicong Hong, Difan Liu +3

The quadratic computational complexity of self-attention in diffusion transformers (DiT) introduces substantial computational costs in high-resolution image generation. While the l…

cs.CV2025

Visual Persona: Foundation Model for Full-Body Human Customization

Jisu Nam, Soowon Son, Zhan Xu +6

We introduce Visual Persona, a foundation model for text-to-image full-body human customization that, given a single in-the-wild human image, generates diverse images of the indivi…

cs.CV2025

VEGGIE: Instructional Editing and Reasoning Video Concepts with Grounded Generation

Shoubin Yu, Difan Liu, Ziqiao Ma +5

Recent video diffusion models have enhanced video editing, but it remains challenging to handle instructional editing and diverse tasks (e.g., adding, removing, changing) within a…

cs.CV2024

Move-in-2D: 2D-Conditioned Human Motion Generation

Hsin-Ping Huang, Yang Zhou, Jui-Hsien Wang +4

Generating realistic human videos remains a challenging task, with the most effective methods currently relying on a human motion sequence as a control signal. Existing approaches…

cs.CV2024

HARIVO: Harnessing Text-to-Image Models for Video Generation

Mingi Kwon, Seoung Wug Oh, Yang Zhou +6

We present a method to create diffusion-based video models from pretrained Text-to-Image (T2I) models. Recently, AnimateDiff proposed freezing the T2I model while only training tem…

cs.CV2024

Progressive Autoregressive Video Diffusion Models

Desai Xie, Zhan Xu, Yicong Hong +5

Current frontier video diffusion models have demonstrated remarkable results at generating high-quality videos. However, they can only generate short video clips, normally around 1…

cs.CV2024★ 3 cited

VideoGigaGAN: Towards Detail-rich Video Super-Resolution

Yiran Xu, Taesung Park, Richard Zhang +5

Video super-resolution (VSR) approaches have shown impressive temporal consistency in upsampled videos. However, these approaches tend to generate blurrier results than their image…

cs.CV2024★ 1 cited

Customize-A-Video: One-Shot Motion Customization of Text-to-Video Diffusion Models

Yixuan Ren, Yang Zhou, Jimei Yang +5

Image customization has been extensively studied in text-to-image (T2I) diffusion models, leading to impressive outcomes and applications. With the emergence of text-to-video (T2V)…