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20152023
most citedSubject-driven Text-to-Image Generation via Apprenticeship Learning

46 citations · 129 across the 10 of their papers we have counts for

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10 papers · 1 filter

cs.CV2023

Controllable One-Shot Face Video Synthesis With Semantic Aware Prior

Kangning Liu, Yu-Chuan Su, Wei +3

The one-shot talking-head synthesis task aims to animate a source image to another pose and expression, which is dictated by a driving frame. Recent methods rely on warping the app…

cs.CV2023★ 5 cited

Identity Encoder for Personalized Diffusion

Yu-Chuan Su, Kelvin C. K. Chan, Yandong Li +5

Many applications can benefit from personalized image generation models, including image enhancement, video conferences, just to name a few. Existing works achieved personalization…

cs.CV2023★ 21 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.CV2023

Federated Learning of Shareable Bases for Personalization-Friendly Image Classification

Hong-You Chen, Jike Zhong, Mingda Zhang +5

Personalized federated learning (PFL) aims to harness the collective wisdom of clients' data while building personalized models tailored to individual clients' data distributions.…

cs.CV2023★ 1 cited

What's in a Name? Beyond Class Indices for Image Recognition

Kai Han, Xiaohu Huang, Yandong Li +3

Existing machine learning models demonstrate excellent performance in image object recognition after training on a large-scale dataset under full supervision. However, these models…

cs.CV2023★ 46 cited

Subject-driven Text-to-Image Generation via Apprenticeship Learning

Wenhu Chen, Hexiang Hu, Yandong Li +4

Recent text-to-image generation models like DreamBooth have made remarkable progress in generating highly customized images of a target subject, by fine-tuning an ``expert model''…

cs.CV2020★ 20 cited

Global Self-Attention Networks for Image Recognition

Zhuoran Shen, Irwan Bello, Raviteja Vemulapalli +2

Recently, a series of works in computer vision have shown promising results on various image and video understanding tasks using self-attention. However, due to the quadratic compu…

cs.CV2020

Boosting Image-based Mutual Gaze Detection using Pseudo 3D Gaze

Bardia Doosti, Ching-Hui Chen, Raviteja Vemulapalli +3

Mutual gaze detection, i.e., predicting whether or not two people are looking at each other, plays an important role in understanding human interactions. In this work, we focus on…

cs.CV2019★ 3 cited

Search to Distill: Pearls are Everywhere but not the Eyes

Yu Liu, Xuhui Jia, Mingxing Tan +4

Standard Knowledge Distillation (KD) approaches distill the knowledge of a cumbersome teacher model into the parameters of a student model with a pre-defined architecture. However,…

cs.CV2015★ 31 cited

An Empirical Study of Recent Face Alignment Methods

Heng Yang, Xuhui Jia, Chen Change Loy +1

The problem of face alignment has been intensively studied in the past years. A large number of novel methods have been proposed and reported very good performance on benchmark dat…