Search Results for author: Hong Chang

Found 23 papers, 13 papers with code

Clothes-Changing Person Re-identification with RGB Modality Only

1 code implementation CVPR 2022 Xinqian Gu, Hong Chang, Bingpeng Ma, Shutao Bai, Shiguang Shan, Xilin Chen

In this paper, we propose a Clothes-based Adversarial Loss (CAL) to mine clothes-irrelevant features from the original RGB images by penalizing the predictive power of re-id model w. r. t.

Person Re-Identification

Joint Feature Learning and Relation Modeling for Tracking: A One-Stream Framework

1 code implementation22 Mar 2022 Botao Ye, Hong Chang, Bingpeng Ma, Shiguang Shan

The current popular two-stream, two-stage tracking framework extracts the template and the search region features separately and then performs relation modeling, thus the extracted features lack the awareness of the target and have limited target-background discriminability.

Visual Object Tracking

Salient-to-Broad Transition for Video Person Re-Identification

1 code implementation CVPR 2022 Shutao Bai, Bingpeng Ma, Hong Chang, Rui Huang, Xilin Chen

To further improve SBM, an Integration-and-Distribution Module (IDM) is introduced to enhance frame-level representations.

Video-Based Person Re-Identification

Feature Completion for Occluded Person Re-Identification

1 code implementation24 Jun 2021 Ruibing Hou, Bingpeng Ma, Hong Chang, Xinqian Gu, Shiguang Shan, Xilin Chen

Our method significantly outperforms existing methods on the occlusion datasets, while remains top even superior performance on holistic datasets.

Person Re-Identification

BiCnet-TKS: Learning Efficient Spatial-Temporal Representation for Video Person Re-Identification

1 code implementation CVPR 2021 Ruibing Hou, Hong Chang, Bingpeng Ma, Rui Huang, Shiguang Shan

Detail Branch processes frames at original resolution to preserve the detailed visual clues, and Context Branch with a down-sampling strategy is employed to capture long-range contexts.

Video-Based Person Re-Identification

Continuity-Discrimination Convolutional Neural Network for Visual Object Tracking

no code implementations18 Apr 2021 Shen Li, Bingpeng Ma, Hong Chang, Shiguang Shan, Xilin Chen

This paper proposes a novel model, named Continuity-Discrimination Convolutional Neural Network (CD-CNN), for visual object tracking.

Visual Object Tracking

IAUnet: Global Context-Aware Feature Learning for Person Re-Identification

1 code implementation2 Sep 2020 Ruibing Hou, Bingpeng Ma, Hong Chang, Xinqian Gu, Shiguang Shan, Xilin Chen

Furthermore, a Channel IAU (CIAU) module is designed to model the semantic contextual interactions between channel features to enhance the feature representation, especially for small-scale visual cues and body parts.

Object Categorization Person Re-Identification

Temporal Complementary Learning for Video Person Re-Identification

2 code implementations ECCV 2020 Ruibing Hou, Hong Chang, Bingpeng Ma, Shiguang Shan, Xilin Chen

This paper proposes a Temporal Complementary Learning Network that extracts complementary features of consecutive video frames for video person re-identification.

Video-Based Person Re-Identification

Appearance-Preserving 3D Convolution for Video-based Person Re-identification

1 code implementation ECCV 2020 Xinqian Gu, Hong Chang, Bingpeng Ma, Hongkai Zhang, Xilin Chen

Due to the imperfect person detection results and posture changes, temporal appearance misalignment is unavoidable in video-based person re-identification (ReID).

Human Detection Video-Based Person Re-Identification

Dynamic R-CNN: Towards High Quality Object Detection via Dynamic Training

3 code implementations ECCV 2020 Hongkai Zhang, Hong Chang, Bingpeng Ma, Naiyan Wang, Xilin Chen

For example, the fixed label assignment strategy and regression loss function cannot fit the distribution change of proposals and thus are harmful to training high quality detectors.

Ranked #73 on Object Detection on COCO test-dev (using extra training data)

object-detection Object Detection

VRSTC: Occlusion-Free Video Person Re-Identification

no code implementations CVPR 2019 Ruibing Hou, Bingpeng Ma, Hong Chang, Xinqian Gu, Shiguang Shan, Xilin Chen

For one thing, the spatial structure of a pedestrian frame can be used to predict the occluded body parts from the unoccluded body parts of this frame.

Video-Based Person Re-Identification

Interaction-and-Aggregation Network for Person Re-identification

1 code implementation CVPR 2019 Ruibing Hou, Bingpeng Ma, Hong Chang, Xinqian Gu, Shiguang Shan, Xilin Chen

Person re-identification (reID) benefits greatly from deep convolutional neural networks (CNNs) which learn robust feature embeddings.

Person Re-Identification

Cascade RetinaNet: Maintaining Consistency for Single-Stage Object Detection

no code implementations16 Jul 2019 Hongkai Zhang, Hong Chang, Bingpeng Ma, Shiguang Shan, Xilin Chen

Recent researches attempt to improve the detection performance by adopting the idea of cascade for single-stage detectors.

General Classification object-detection +1

Visual relationship detection with deep structural ranking

1 code implementation27 Apr 2018 Kongming Liang, Yuhong Guo, Hong Chang, Xilin Chen

In this paper, we propose a novel framework, called Deep Structural Ranking, for visual relationship detection.

Visual Relationship Detection

Robust path-based spectral clustering

no code implementations1 Jan 2018 Hong Chang, Dit-yan Yeung

In this paper, based on M-estimation from robust statistics, we develop a robust path-based spectral clustering method by defining a robust path-based similarity measure for spectral clustering under both unsupervised and semi-supervised settings.

Image Segmentation Semantic Segmentation

Super-Resolution with Deep Adaptive Image Resampling

no code implementations18 Dec 2017 Xu Jia, Hong Chang, Tinne Tuytelaars

In this work, we revisit the more traditional interpolation-based methods, that were popular before, now with the help of deep learning.

Image Super-Resolution Single Image Super Resolution

Generalized Unsupervised Manifold Alignment

no code implementations NeurIPS 2014 Zhen Cui, Hong Chang, Shiguang Shan, Xilin Chen

In this paper, we propose a generalized Unsupervised Manifold Alignment (GUMA) method to build the connections between different but correlated datasets without any known correspondences.

Stacked Progressive Auto-Encoders (SPAE) for Face Recognition Across Poses

no code implementations CVPR 2014 Meina Kan, Shiguang Shan, Hong Chang, Xilin Chen

Identifying subjects with variations caused by poses is one of the most challenging tasks in face recognition, since the difference in appearances caused by poses may be even larger than the difference due to identity.

Face Recognition Pose Estimation

Deeply Coupled Auto-encoder Networks for Cross-view Classification

no code implementations10 Feb 2014 Wen Wang, Zhen Cui, Hong Chang, Shiguang Shan, Xilin Chen

In this paper, we propose a simple but effective coupled neural network, called Deeply Coupled Autoencoder Networks (DCAN), which seeks to build two deep neural networks, coupled with each other in every corresponding layers.

Classification Denoising +2

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