activity
20222024
most citedTaming Encoder for Zero Fine-tuning Image Customization with Text-to-Image Diffusion Models

21 citations · 26 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2024

3D Congealing: 3D-Aware Image Alignment in the Wild

Yunzhi Zhang, Zizhang Li, Amit Raj +5

We propose 3D Congealing, a novel problem of 3D-aware alignment for 2D images capturing semantically similar objects. Given a collection of unlabeled Internet images, our goal is t…

cs.LG20242 cited

PRDP: Proximal Reward Difference Prediction for Large-Scale Reward Finetuning of Diffusion Models

Fei Deng, Qifei Wang, Wei Wei +2

Reward finetuning has emerged as a promising approach to aligning foundation models with downstream objectives. Remarkable success has been achieved in the language domain by using…

cs.CV2023

Towards Authentic Face Restoration with Iterative Diffusion Models and Beyond

Yang Zhao, Tingbo Hou, Yu-Chuan Su +2

An authentic face restoration system is becoming increasingly demanding in many computer vision applications, e.g., image enhancement, video communication, and taking portrait. Mos…

cs.CV20231 cited

CLIP3Dstyler: Language Guided 3D Arbitrary Neural Style Transfer

Ming Gao, YanWu Xu, Yang Zhao +3

In this paper, we propose a novel language-guided 3D arbitrary neural style transfer method (CLIP3Dstyler). We aim at stylizing any 3D scene with an arbitrary style from a text des…

cs.CV202321 cited

Taming Encoder for Zero Fine-tuning Image Customization with Text-to-Image Diffusion Models

Xuhui Jia, Yang Zhao, Kelvin C. K. Chan +6

This paper proposes a method for generating images of customized objects specified by users. The method is based on a general framework that bypasses the lengthy optimization requi…

cs.CV20222 cited

Efficient Heterogeneous Video Segmentation at the Edge

Jamie Menjay Lin, Siargey Pisarchyk, Juhyun Lee +7

We introduce an efficient video segmentation system for resource-limited edge devices leveraging heterogeneous compute. Specifically, we design network models by searching across m…