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20232026
most citedCameraCtrl: Enabling Camera Control for Text-to-Video Generation

3 citations · 3 across the 6 of their papers we have counts for

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cs.CV2026

DSAQuant: Denoising-Stage-Aligned Quantization-Aware Training for Video Generation

Shuaiting Li, Zelin Gao, Haibin Shen +3

Video diffusion models (VDMs) have achieved impressive progress in text-to-video generation, but their high memory and computational costs hinder practical deployment. Quantization…

cs.CV2025

RelightVid: Temporal-Consistent Diffusion Model for Video Relighting

Ye Fang, Zeyi Sun, Shangzhan Zhang +6

Diffusion models have demonstrated remarkable success in image generation and editing, with recent advancements enabling albedo-preserving image relighting. However, applying these…

cs.CV2024

FiVA: Fine-grained Visual Attribute Dataset for Text-to-Image Diffusion Models

Tong Wu, Yinghao Xu, Ryan Po +6

Recent advances in text-to-image generation have enabled the creation of high-quality images with diverse applications. However, accurately describing desired visual attributes can…

cs.CV2024★ 3 cited

CameraCtrl: Enabling Camera Control for Text-to-Video Generation

Hao He, Yinghao Xu, Yuwei Guo +4

Controllability plays a crucial role in video generation, as it allows users to create and edit content more precisely. Existing models, however, lack control of camera pose that s…

cs.CV2023

Learning Naturally Aggregated Appearance for Efficient 3D Editing

Ka Leong Cheng, Qiuyu Wang, Zifan Shi +5

Neural radiance fields, which represent a 3D scene as a color field and a density field, have demonstrated great progress in novel view synthesis yet are unfavorable for editing du…

cs.CV2023

Gaussian Shell Maps for Efficient 3D Human Generation

Rameen Abdal, Wang Yifan, Zifan Shi +6

Efficient generation of 3D digital humans is important in several industries, including virtual reality, social media, and cinematic production. 3D generative adversarial networks…