1.6k citations · 1.6k across the 7 of their papers we have counts for
7 papers
VEnhancer: Generative Space-Time Enhancement for Video Generation
Jingwen He, Tianfan Xue, Dongyang Liu +6
We present VEnhancer, a generative space-time enhancement framework that improves the existing text-to-video results by adding more details in spatial domain and synthetic detailed…
LenslessFace: An End-to-End Optimized Lensless System for Privacy-Preserving Face Verification
Xin Cai, Hailong Zhang, Chenchen Wang +3
Lensless cameras, innovatively replacing traditional lenses for ultra-thin, flat optics, encode light directly onto sensors, producing images that are not immediately recognizable.…
Interactive3D: Create What You Want by Interactive 3D Generation
Shaocong Dong, Lihe Ding, Zhanpeng Huang +3
3D object generation has undergone significant advancements, yielding high-quality results. However, fall short of achieving precise user control, often yielding results that do no…
HDRFlow: Real-Time HDR Video Reconstruction with Large Motions
Gangwei Xu, Yujin Wang, Jinwei Gu +2
Reconstructing High Dynamic Range (HDR) video from image sequences captured with alternating exposures is challenging, especially in the presence of large camera or object motion.…
Reconstruct-and-Generate Diffusion Model for Detail-Preserving Image Denoising
Yujin Wang, Lingen Li, Tianfan Xue +1
Image denoising is a fundamental and challenging task in the field of computer vision. Most supervised denoising methods learn to reconstruct clean images from noisy inputs, which…
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling
Jiajun Wu, Chengkai Zhang, Tianfan Xue +2
We study the problem of 3D object generation. We propose a novel framework, namely 3D Generative Adversarial Network (3D-GAN), which generates 3D objects from a probabilistic space…