Search Results for author: Huabin Zheng

Found 7 papers, 4 papers with code

SEPT: Towards Scalable and Efficient Visual Pre-Training

no code implementations11 Dec 2022 Yiqi Lin, Huabin Zheng, Huaping Zhong, Jinjing Zhu, Weijia Li, Conghui He, Lin Wang

To address these issues, we build a task-specific self-supervised pre-training framework from a data selection perspective based on a simple hypothesis that pre-training on the unlabeled samples with similar distribution to the target task can bring substantial performance gains.


Semantically Coherent Out-of-Distribution Detection

2 code implementations ICCV 2021 Jingkang Yang, Haoqi Wang, Litong Feng, Xiaopeng Yan, Huabin Zheng, Wayne Zhang, Ziwei Liu

The proposed UDG can not only enrich the semantic knowledge of the model by exploiting unlabeled data in an unsupervised manner, but also distinguish ID/OOD samples to enhance ID classification and OOD detection tasks simultaneously.

Out-of-Distribution Detection Out of Distribution (OOD) Detection

Progressive Representative Labeling for Deep Semi-Supervised Learning

no code implementations13 Aug 2021 Xiaopeng Yan, Riquan Chen, Litong Feng, Jingkang Yang, Huabin Zheng, Wayne Zhang

In this paper, we propose to label only the most representative samples to expand the labeled set.

Webly Supervised Image Classification with Metadata: Automatic Noisy Label Correction via Visual-Semantic Graph

1 code implementation12 Oct 2020 Jingkang Yang, Weirong Chen, Litong Feng, Xiaopeng Yan, Huabin Zheng, Wayne Zhang

VSGraph-LC starts from anchor selection referring to the semantic similarity between metadata and correct label concepts, and then propagates correct labels from anchors on a visual graph using graph neural network (GNN).

General Classification Image Classification +2

Toward Characteristic-Preserving Image-based Virtual Try-On Network

5 code implementations ECCV 2018 Bochao Wang, Huabin Zheng, Xiaodan Liang, Yimin Chen, Liang Lin, Meng Yang

Second, to alleviate boundary artifacts of warped clothes and make the results more realistic, we employ a Try-On Module that learns a composition mask to integrate the warped clothes and the rendered image to ensure smoothness.

Geometric Matching Virtual Try-on

Chinese/English mixed Character Segmentation as Semantic Segmentation

no code implementations7 Nov 2016 Huabin Zheng, Jingyu Wang, Zhengjie Huang, Yang Yang, Rong pan

We take advantage of the successful architecture called fully convolutional networks (FCN) in the field of semantic segmentation.

Optical Character Recognition (OCR) Position +2

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