Search Results for author: Wei-Hong Li

Found 12 papers, 8 papers with code

Universal Representations: A Unified Look at Multiple Task and Domain Learning

2 code implementations6 Apr 2022 Wei-Hong Li, Xialei Liu, Hakan Bilen

We propose a unified look at jointly learning multiple vision tasks and visual domains through universal representations, a single deep neural network.

cross-domain few-shot learning Image Classification

Learning Multiple Dense Prediction Tasks from Partially Annotated Data

1 code implementation CVPR 2022 Wei-Hong Li, Xialei Liu, Hakan Bilen

Despite the recent advances in multi-task learning of dense prediction problems, most methods rely on expensive labelled datasets.

Multi-Task Learning

Cross-domain Few-shot Learning with Task-specific Adapters

2 code implementations CVPR 2022 Wei-Hong Li, Xialei Liu, Hakan Bilen

In this paper, we look at the problem of cross-domain few-shot classification that aims to learn a classifier from previously unseen classes and domains with few labeled samples.

cross-domain few-shot learning Few-Shot Image Classification

Universal Representation Learning from Multiple Domains for Few-shot Classification

3 code implementations ICCV 2021 Wei-Hong Li, Xialei Liu, Hakan Bilen

In this paper, we look at the problem of few-shot classification that aims to learn a classifier for previously unseen classes and domains from few labeled samples.

Classification Few-Shot Image Classification +2

MINI-Net: Multiple Instance Ranking Network for Video Highlight Detection

no code implementations ECCV 2020 Fa-Ting Hong, Xuanteng Huang, Wei-Hong Li, Wei-Shi Zheng

We address the weakly supervised video highlight detection problem for learning to detect segments that are more attractive in training videos given their video event label but without expensive supervision of manually annotating highlight segments.

Highlight Detection

Knowledge Distillation for Multi-task Learning

3 code implementations14 Jul 2020 Wei-Hong Li, Hakan Bilen

We then learn the multi-task model for minimizing task-specific loss and for producing the same feature with task-specific models.

Knowledge Distillation Multi-Task Learning

Learning to Detect Important People in Unlabelled Images for Semi-supervised Important People Detection

1 code implementation CVPR 2020 Fa-Ting Hong, Wei-Hong Li, Wei-Shi Zheng

Important people detection is to automatically detect the individuals who play the most important roles in a social event image, which requires the designed model to understand a high-level pattern.

Object Recognition Pseudo Label

Learning to Impute: A General Framework for Semi-supervised Learning

2 code implementations22 Dec 2019 Wei-Hong Li, Chuan-Sheng Foo, Hakan Bilen

Recent semi-supervised learning methods have shown to achieve comparable results to their supervised counterparts while using only a small portion of labels in image classification tasks thanks to their regularization strategies.

Classification Facial Landmark Detection +2

Towards Photo-Realistic Visible Watermark Removal with Conditional Generative Adversarial Networks

no code implementations30 May 2019 Xiang Li, Chan Lu, Danni Cheng, Wei-Hong Li, Mei Cao, Bo Liu, Jiechao Ma, Wei-Shi Zheng

Visible watermark plays an important role in image copyright protection and the robustness of a visible watermark to an attack is shown to be essential.

Image-to-Image Translation

Learning to Learn Relation for Important People Detection in Still Images

1 code implementation CVPR 2019 Wei-Hong Li, Fa-Ting Hong, Wei-Shi Zheng

In this work, we propose a deep imPOrtance relatIon NeTwork (POINT) that combines both relation modeling and feature learning.

One-pass Person Re-identification by Sketch Online Discriminant Analysis

no code implementations9 Nov 2017 Wei-Hong Li, Zhuowei Zhong, Wei-Shi Zheng

While there is a few work on discussing online re-id, most of them require considerable storage of all passed data samples that have been ever observed, and this could be unrealistic for processing data from a large camera network.

Person Re-Identification

PersonRank: Detecting Important People in Images

no code implementations6 Nov 2017 Wei-Hong Li, Benchao Li, Wei-Shi Zheng

Always, some individuals in images are more important/attractive than others in some events such as presentation, basketball game or speech.

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