Search Results for author: Changxing Ding

Found 44 papers, 28 papers with code

Polysemy Deciphering Network for Human-Object Interaction Detection

1 code implementation ECCV 2020 Xubin Zhong, Changxing Ding, Xian Qu, DaCheng Tao

First, PD-Net augments human pose and spatial features for HOI detection using language priors, enabling the verb classifiers to receive language hints that reduce the intra-class variation of the same verb.

Human-Object Interaction Detection Scene Understanding

Disentangled Interaction Representation for One-Stage Human-Object Interaction Detection

no code implementations4 Dec 2023 Xubin Zhong, Changxing Ding, Yupeng Hu, DaCheng Tao

In this paper, we improve the performance of one-stage methods by enabling them to extract disentangled interaction representations.

Human-Object Interaction Detection Pose Estimation

Unified Pre-training with Pseudo Texts for Text-To-Image Person Re-identification

1 code implementation ICCV 2023 Zhiyin Shao, Xinyu Zhang, Changxing Ding, Jian Wang, Jingdong Wang

In this way, the pre-training task and the T2I-ReID task are made consistent with each other on both data and training levels.

Person Re-Identification

DARC: Distribution-Aware Re-Coloring Model for Generalizable Nucleus Segmentation

no code implementations1 Sep 2023 Shengcong Chen, Changxing Ding, DaCheng Tao, Hao Chen

Second, we propose a new instance normalization method that is robust to the variation in foreground-background ratios.


Can Linguistic Knowledge Improve Multimodal Alignment in Vision-Language Pretraining?

1 code implementation24 Aug 2023 Fei Wang, Liang Ding, Jun Rao, Ye Liu, Li Shen, Changxing Ding

The multimedia community has shown a significant interest in perceiving and representing the physical world with multimodal pretrained neural network models, and among them, the visual-language pertaining (VLP) is, currently, the most captivating topic.

Cross-modal & Cross-domain Learning for Unsupervised LiDAR Semantic Segmentation

no code implementations5 Aug 2023 Yiyang Chen, Shanshan Zhao, Changxing Ding, Liyao Tang, Chaoyue Wang, DaCheng Tao

In recent years, cross-modal domain adaptation has been studied on the paired 2D image and 3D LiDAR data to ease the labeling costs for 3D LiDAR semantic segmentation (3DLSS) in the target domain.

Domain Adaptation LIDAR Semantic Segmentation +1

MMoT: Mixture-of-Modality-Tokens Transformer for Composed Multimodal Conditional Image Synthesis

no code implementations10 May 2023 Jianbin Zheng, Daqing Liu, Chaoyue Wang, Minghui Hu, Zuopeng Yang, Changxing Ding, DaCheng Tao

To this end, we propose to generate images conditioned on the compositions of multimodal control signals, where modalities are imperfectly complementary, i. e., composed multimodal conditional image synthesis (CMCIS).

Image Generation

Mining False Positive Examples for Text-Based Person Re-identification

1 code implementation15 Mar 2023 Wenhao Xu, Zhiyin Shao, Changxing Ding

Text-based person re-identification (ReID) aims to identify images of the targeted person from a large-scale person image database according to a given textual description.

Person Re-Identification

Harmonious Feature Learning for Interactive Hand-Object Pose Estimation

1 code implementation CVPR 2023 Zhifeng Lin, Changxing Ding, Huan Yao, Zengsheng Kuang, Shaoli Huang

Notably, the performance of our model on hand pose estimation even surpasses that of existing works that only perform the single-hand pose estimation task.

hand-object pose Hand Pose Estimation

Learning Granularity-Unified Representations for Text-to-Image Person Re-identification

2 code implementations16 Jul 2022 Zhiyin Shao, Xinyu Zhang, Meng Fang, Zhifeng Lin, Jian Wang, Changxing Ding

In PGU, we adopt a set of shared and learnable prototypes as the queries to extract diverse and semantically aligned features for both modalities in the granularity-unified feature space, which further promotes the ReID performance.

Person Re-Identification Text based Person Retrieval +1

Category-Level 6D Object Pose and Size Estimation using Self-Supervised Deep Prior Deformation Networks

1 code implementation12 Jul 2022 Jiehong Lin, Zewei Wei, Changxing Ding, Kui Jia

It is difficult to precisely annotate object instances and their semantics in 3D space, and as such, synthetic data are extensively used for these tasks, e. g., category-level 6D object pose and size estimation.

6D Pose Estimation Unsupervised Domain Adaptation

Towards Hard-Positive Query Mining for DETR-based Human-Object Interaction Detection

1 code implementation12 Jul 2022 Xubin Zhong, Changxing Ding, Zijian Li, Shaoli Huang

Specifically, we shift the GT bounding boxes of each labeled human-object pair so that the shifted boxes cover only a certain portion of the GT ones.

Human-Object Interaction Detection

1st Place Solution to the EPIC-Kitchens Action Anticipation Challenge 2022

no code implementations10 Jul 2022 Zeyu Jiang, Changxing Ding

In this report, we describe the technical details of our submission to the EPIC-Kitchens Action Anticipation Challenge 2022.

Action Anticipation Knowledge Distillation

Style Interleaved Learning for Generalizable Person Re-identification

1 code implementation7 Jul 2022 Wentao Tan, Changxing Ding, Pengfei Wang, Mingming Gong, Kui Jia

This common practice causes the model to overfit to existing feature styles in the source domain, resulting in sub-optimal generalization ability on target domains.

Domain Generalization Generalizable Person Re-identification +1

Context Sensing Attention Network for Video-based Person Re-identification

no code implementations6 Jul 2022 Kan Wang, Changxing Ding, Jianxin Pang, Xiangmin Xu

In this work, we propose a novel Context Sensing Attention Network (CSA-Net), which improves both the frame feature extraction and temporal aggregation steps.

Video-Based Person Re-Identification

Few-Shot Head Swapping in the Wild

no code implementations CVPR 2022 Changyong Shu, Hemao Wu, Hang Zhou, Jiaming Liu, Zhibin Hong, Changxing Ding, Junyu Han, Jingtuo Liu, Errui Ding, Jingdong Wang

Particularly, seamless blending is achieved with the help of a Semantic-Guided Color Reference Creation procedure and a Blending UNet.

Face Swapping

MobileFaceSwap: A Lightweight Framework for Video Face Swapping

1 code implementation11 Jan 2022 Zhiliang Xu, Zhibin Hong, Changxing Ding, Zhen Zhu, Junyu Han, Jingtuo Liu, Errui Ding

In this work, we propose a lightweight Identity-aware Dynamic Network (IDN) for subject-agnostic face swapping by dynamically adjusting the model parameters according to the identity information.

Face Swapping Knowledge Distillation

Quality-aware Part Models for Occluded Person Re-identification

no code implementations1 Jan 2022 Pengfei Wang, Changxing Ding, Zhiyin Shao, Zhibin Hong, Shengli Zhang, DaCheng Tao

Existing approaches typically rely on outside tools to infer visible body parts, which may be suboptimal in terms of both computational efficiency and ReID accuracy.

Person Re-Identification

Uncertainty-aware Clustering for Unsupervised Domain Adaptive Object Re-identification

1 code implementation22 Aug 2021 Pengfei Wang, Changxing Ding, Wentao Tan, Mingming Gong, Kui Jia, DaCheng Tao

In particular, the performance of our unsupervised UCF method in the MSMT17$\to$Market1501 task is better than that of the fully supervised setting on Market1501.


Semantically Self-Aligned Network for Text-to-Image Part-aware Person Re-identification

1 code implementation27 Jul 2021 Zefeng Ding, Changxing Ding, Zhiyin Shao, DaCheng Tao

Third, we introduce a Compound Ranking (CR) loss that makes use of textual descriptions for other images of the same identity to provide extra supervision, thereby effectively reducing the intra-class variance in textual features.

Image Retrieval Person Re-Identification +1

Attention-guided Progressive Mapping for Profile Face Recognition

1 code implementation27 Jun 2021 Junyang Huang, Changxing Ding

Firstly, to reduce the difficulty of directly transforming the profile face features into a frontal pose, we propose to learn the feature residual between the source pose and its nearby pose in a block-byblock fashion, and thus traversing to the feature space of a smaller pose by adding the learned residual.

Face Recognition

Glance and Gaze: Inferring Action-aware Points for One-Stage Human-Object Interaction Detection

1 code implementation CVPR 2021 Xubin Zhong, Xian Qu, Changxing Ding, DaCheng Tao

In this paper, we propose a novel one-stage method, namely Glance and Gaze Network (GGNet), which adaptively models a set of actionaware points (ActPoints) via glance and gaze steps.

Human-Object Interaction Detection

On Universal Black-Box Domain Adaptation

1 code implementation10 Apr 2021 Bin Deng, Yabin Zhang, Hui Tang, Changxing Ding, Kui Jia

The great promise that UB$^2$DA makes, however, brings significant learning challenges, since domain adaptation can only rely on the predictions of unlabeled target data in a partially overlapped label space, by accessing the interface of source model.

Universal Domain Adaptation

CPP-Net: Context-aware Polygon Proposal Network for Nucleus Segmentation

1 code implementation13 Feb 2021 Shengcong Chen, Changxing Ding, Minfeng Liu, Jun Cheng, DaCheng Tao

Each polygon is represented by a set of centroid-to-boundary distances, which are in turn predicted by features of the centroid pixel for a single nucleus.


Classification of Single-View Object Point Clouds

no code implementations18 Dec 2020 Zelin Xu, Ke Chen, KangJun Liu, Changxing Ding, YaoWei Wang, Kui Jia

By adapting existing ModelNet40 and ScanNet datasets to the single-view, partial setting, experiment results can verify the necessity of object pose estimation and superiority of our PAPNet to existing classifiers.

3D Object Classification 6D Pose Estimation using RGB +5

Batch Coherence-Driven Network for Part-aware Person Re-Identification

no code implementations21 Sep 2020 Kan Wang, Pengfei Wang, Changxing Ding, DaCheng Tao

First, we introduce a batch coherence-guided channel attention (BCCA) module that highlights the relevant channels for each respective part from the output of a deep backbone model.

Person Re-Identification

Polysemy Deciphering Network for Robust Human-Object Interaction Detection

2 code implementations7 Aug 2020 Xubin Zhong, Changxing Ding, Xian Qu, DaCheng Tao

To address this issue, in this paper, we propose a novel Polysemy Deciphering Network (PD-Net) that decodes the visual polysemy of verbs for HOI detection in three distinct ways.

Human-Object Interaction Detection Scene Understanding

Boundary-assisted Region Proposal Networks for Nucleus Segmentation

1 code implementation4 Jun 2020 Shengcong Chen, Changxing Ding, DaCheng Tao

Accordingly, in this paper, we devise a Boundary-assisted Region Proposal Network (BRP-Net) that achieves robust instance-level nucleus segmentation.

Boundary Detection Instance Segmentation +3

Learning Oracle Attention for High-fidelity Face Completion

no code implementations CVPR 2020 Tong Zhou, Changxing Ding, Shaowen Lin, Xinchao Wang, DaCheng Tao

While recent works adopted the attention mechanism to learn the contextual relations among elements of the face, they have largely overlooked the disastrous impacts of inaccurate attention scores; in addition, they fail to pay sufficient attention to key facial components, the completion results of which largely determine the authenticity of a face image.

Facial Inpainting Vocal Bursts Intensity Prediction

GPS-Net: Graph Property Sensing Network for Scene Graph Generation

1 code implementation CVPR 2020 Xin Lin, Changxing Ding, Jinquan Zeng, DaCheng Tao

There are three key properties of scene graph that have been underexplored in recent works: namely, the edge direction information, the difference in priority between nodes, and the long-tailed distribution of relationships.

Graph Generation Scene Graph Generation

Multi-task Learning with Coarse Priors for Robust Part-aware Person Re-identification

1 code implementation18 Mar 2020 Changxing Ding, Kan Wang, Pengfei Wang, DaCheng Tao

MPN has three key advantages: 1) it does not need to conduct body part detection in the inference stage; 2) its model is very compact and efficient for both training and testing; 3) in the training stage, it requires only coarse priors of body part locations, which are easy to obtain.

Multi-Task Learning Person Re-Identification

Soft-ranking Label Encoding for Robust Facial Age Estimation

no code implementations9 Jun 2019 Xusheng Zeng, Changxing Ding, Yonggang Wen, DaCheng Tao

Moreover, we also carefully analyze existing evaluation protocols for age estimation, finding that the overlap in identity between the training and testing sets affects the relative performance of different age encoding methods.

Age Estimation MORPH

One-pass Multi-task Networks with Cross-task Guided Attention for Brain Tumor Segmentation

1 code implementation5 Jun 2019 Chenhong Zhou, Changxing Ding, Xinchao Wang, Zhentai Lu, DaCheng Tao

The model cascade (MC) strategy significantly alleviates the class imbalance issue via running a set of individual deep models for coarse-to-fine segmentation.

Brain Tumor Segmentation Image Segmentation +2

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

1 code implementation5 Nov 2018 Spyridon Bakas, Mauricio Reyes, Andras Jakab, Stefan Bauer, Markus Rempfler, Alessandro Crimi, Russell Takeshi Shinohara, Christoph Berger, Sung Min Ha, Martin Rozycki, Marcel Prastawa, Esther Alberts, Jana Lipkova, John Freymann, Justin Kirby, Michel Bilello, Hassan Fathallah-Shaykh, Roland Wiest, Jan Kirschke, Benedikt Wiestler, Rivka Colen, Aikaterini Kotrotsou, Pamela Lamontagne, Daniel Marcus, Mikhail Milchenko, Arash Nazeri, Marc-Andre Weber, Abhishek Mahajan, Ujjwal Baid, Elizabeth Gerstner, Dongjin Kwon, Gagan Acharya, Manu Agarwal, Mahbubul Alam, Alberto Albiol, Antonio Albiol, Francisco J. Albiol, Varghese Alex, Nigel Allinson, Pedro H. A. Amorim, Abhijit Amrutkar, Ganesh Anand, Simon Andermatt, Tal Arbel, Pablo Arbelaez, Aaron Avery, Muneeza Azmat, Pranjal B., W Bai, Subhashis Banerjee, Bill Barth, Thomas Batchelder, Kayhan Batmanghelich, Enzo Battistella, Andrew Beers, Mikhail Belyaev, Martin Bendszus, Eze Benson, Jose Bernal, Halandur Nagaraja Bharath, George Biros, Sotirios Bisdas, James Brown, Mariano Cabezas, Shilei Cao, Jorge M. Cardoso, Eric N Carver, Adrià Casamitjana, Laura Silvana Castillo, Marcel Catà, Philippe Cattin, Albert Cerigues, Vinicius S. Chagas, Siddhartha Chandra, Yi-Ju Chang, Shiyu Chang, Ken Chang, Joseph Chazalon, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Chen, Kun Cheng, Ahana Roy Choudhury, Roger Chylla, Albert Clérigues, Steven Colleman, Ramiro German Rodriguez Colmeiro, Marc Combalia, Anthony Costa, Xiaomeng Cui, Zhenzhen Dai, Lutao Dai, Laura Alexandra Daza, Eric Deutsch, Changxing Ding, Chao Dong, Shidu Dong, Wojciech Dudzik, Zach Eaton-Rosen, Gary Egan, Guilherme Escudero, Théo Estienne, Richard Everson, Jonathan Fabrizio, Yong Fan, Longwei Fang, Xue Feng, Enzo Ferrante, Lucas Fidon, Martin Fischer, Andrew P. French, Naomi Fridman, Huan Fu, David Fuentes, Yaozong Gao, Evan Gates, David Gering, Amir Gholami, Willi Gierke, Ben Glocker, Mingming Gong, Sandra González-Villá, T. Grosges, Yuanfang Guan, Sheng Guo, Sudeep Gupta, Woo-Sup Han, Il Song Han, Konstantin Harmuth, Huiguang He, Aura Hernández-Sabaté, Evelyn Herrmann, Naveen Himthani, Winston Hsu, Cheyu Hsu, Xiaojun Hu, Xiaobin Hu, Yan Hu, Yifan Hu, Rui Hua, Teng-Yi Huang, Weilin Huang, Sabine Van Huffel, Quan Huo, Vivek HV, Khan M. Iftekharuddin, Fabian Isensee, Mobarakol Islam, Aaron S. Jackson, Sachin R. Jambawalikar, Andrew Jesson, Weijian Jian, Peter Jin, V Jeya Maria Jose, Alain Jungo, B Kainz, Konstantinos Kamnitsas, Po-Yu Kao, Ayush Karnawat, Thomas Kellermeier, Adel Kermi, Kurt Keutzer, Mohamed Tarek Khadir, Mahendra Khened, Philipp Kickingereder, Geena Kim, Nik King, Haley Knapp, Urspeter Knecht, Lisa Kohli, Deren Kong, Xiangmao Kong, Simon Koppers, Avinash Kori, Ganapathy Krishnamurthi, Egor Krivov, Piyush Kumar, Kaisar Kushibar, Dmitrii Lachinov, Tryphon Lambrou, Joon Lee, Chengen Lee, Yuehchou Lee, M Lee, Szidonia Lefkovits, Laszlo Lefkovits, James Levitt, Tengfei Li, Hongwei Li, Hongyang Li, Xiaochuan Li, Yuexiang Li, Heng Li, Zhenye Li, Xiaoyu Li, Zeju Li, Xiaogang Li, Wenqi Li, Zheng-Shen Lin, Fengming Lin, Pietro Lio, Chang Liu, Boqiang Liu, Xiang Liu, Mingyuan Liu, Ju Liu, Luyan Liu, Xavier Llado, Marc Moreno Lopez, Pablo Ribalta Lorenzo, Zhentai Lu, Lin Luo, Zhigang Luo, Jun Ma, Kai Ma, Thomas Mackie, Anant Madabushi, Issam Mahmoudi, Klaus H. Maier-Hein, Pradipta Maji, CP Mammen, Andreas Mang, B. S. Manjunath, Michal Marcinkiewicz, S McDonagh, Stephen McKenna, Richard McKinley, Miriam Mehl, Sachin Mehta, Raghav Mehta, Raphael Meier, Christoph Meinel, Dorit Merhof, Craig Meyer, Robert Miller, Sushmita Mitra, Aliasgar Moiyadi, David Molina-Garcia, Miguel A. B. Monteiro, Grzegorz Mrukwa, Andriy Myronenko, Jakub Nalepa, Thuyen Ngo, Dong Nie, Holly Ning, Chen Niu, Nicholas K Nuechterlein, Eric Oermann, Arlindo Oliveira, Diego D. C. Oliveira, Arnau Oliver, Alexander F. I. Osman, Yu-Nian Ou, Sebastien Ourselin, Nikos Paragios, Moo Sung Park, Brad Paschke, J. Gregory Pauloski, Kamlesh Pawar, Nick Pawlowski, Linmin Pei, Suting Peng, Silvio M. Pereira, Julian Perez-Beteta, Victor M. Perez-Garcia, Simon Pezold, Bao Pham, Ashish Phophalia, Gemma Piella, G. N. Pillai, Marie Piraud, Maxim Pisov, Anmol Popli, Michael P. Pound, Reza Pourreza, Prateek Prasanna, Vesna Prkovska, Tony P. Pridmore, Santi Puch, Élodie Puybareau, Buyue Qian, Xu Qiao, Martin Rajchl, Swapnil Rane, Michael Rebsamen, Hongliang Ren, Xuhua Ren, Karthik Revanuru, Mina Rezaei, Oliver Rippel, Luis Carlos Rivera, Charlotte Robert, Bruce Rosen, Daniel Rueckert, Mohammed Safwan, Mostafa Salem, Joaquim Salvi, Irina Sanchez, Irina Sánchez, Heitor M. Santos, Emmett Sartor, Dawid Schellingerhout, Klaudius Scheufele, Matthew R. Scott, Artur A. Scussel, Sara Sedlar, Juan Pablo Serrano-Rubio, N. Jon Shah, Nameetha Shah, Mazhar Shaikh, B. Uma Shankar, Zeina Shboul, Haipeng Shen, Dinggang Shen, Linlin Shen, Haocheng Shen, Varun Shenoy, Feng Shi, Hyung Eun Shin, Hai Shu, Diana Sima, M Sinclair, Orjan Smedby, James M. Snyder, Mohammadreza Soltaninejad, Guidong Song, Mehul Soni, Jean Stawiaski, Shashank Subramanian, Li Sun, Roger Sun, Jiawei Sun, Kay Sun, Yu Sun, Guoxia Sun, Shuang Sun, Yannick R Suter, Laszlo Szilagyi, Sanjay Talbar, DaCheng Tao, Zhongzhao Teng, Siddhesh Thakur, Meenakshi H Thakur, Sameer Tharakan, Pallavi Tiwari, Guillaume Tochon, Tuan Tran, Yuhsiang M. Tsai, Kuan-Lun Tseng, Tran Anh Tuan, Vadim Turlapov, Nicholas Tustison, Maria Vakalopoulou, Sergi Valverde, Rami Vanguri, Evgeny Vasiliev, Jonathan Ventura, Luis Vera, Tom Vercauteren, C. A. Verrastro, Lasitha Vidyaratne, Veronica Vilaplana, Ajeet Vivekanandan, Qian Wang, Chiatse J. Wang, Wei-Chung Wang, Duo Wang, Ruixuan Wang, Yuanyuan Wang, Chunliang Wang, Guotai Wang, Ning Wen, Xin Wen, Leon Weninger, Wolfgang Wick, Shaocheng Wu, Qiang Wu, Yihong Wu, Yong Xia, Yanwu Xu, Xiaowen Xu, Peiyuan Xu, Tsai-Ling Yang, Xiaoping Yang, Hao-Yu Yang, Junlin Yang, Haojin Yang, Guang Yang, Hongdou Yao, Xujiong Ye, Changchang Yin, Brett Young-Moxon, Jinhua Yu, Xiangyu Yue, Songtao Zhang, Angela Zhang, Kun Zhang, Xue-jie Zhang, Lichi Zhang, Xiaoyue Zhang, Yazhuo Zhang, Lei Zhang, Jian-Guo Zhang, Xiang Zhang, Tianhao Zhang, Sicheng Zhao, Yu Zhao, Xiaomei Zhao, Liang Zhao, Yefeng Zheng, Liming Zhong, Chenhong Zhou, Xiaobing Zhou, Fan Zhou, Hongtu Zhu, Jin Zhu, Ying Zhuge, Weiwei Zong, Jayashree Kalpathy-Cramer, Keyvan Farahani, Christos Davatzikos, Koen van Leemput, Bjoern Menze

This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i. e., 2012-2018.

Brain Tumor Segmentation Survival Prediction +1

Correcting the Triplet Selection Bias for Triplet Loss

1 code implementation ECCV 2018 Baosheng Yu, Tongliang Liu, Mingming Gong, Changxing Ding, DaCheng Tao

Considering that the number of triplets grows cubically with the size of training data, triplet mining is thus indispensable for efficiently training with triplet loss.

Face Recognition Fine-Grained Image Classification +5

Trunk-Branch Ensemble Convolutional Neural Networks for Video-based Face Recognition

no code implementations19 Jul 2016 Changxing Ding, DaCheng Tao

Second, to enhance robustness of CNN features to pose variations and occlusion, we propose a Trunk-Branch Ensemble CNN model (TBE-CNN), which extracts complementary information from holistic face images and patches cropped around facial components.

Face Recognition Person Recognition

Robust Face Recognition via Multimodal Deep Face Representation

no code implementations1 Sep 2015 Changxing Ding, DaCheng Tao

The proposed deep learning structure is composed of a set of elaborately designed convolutional neural networks (CNNs) and a three-layer stacked auto-encoder (SAE).

Face Recognition Robust Face Recognition

A Comprehensive Survey on Pose-Invariant Face Recognition

1 code implementation15 Feb 2015 Changxing Ding, DaCheng Tao

The capacity to recognize faces under varied poses is a fundamental human ability that presents a unique challenge for computer vision systems.

Face Generation Face Recognition +1

Multi-Directional Multi-Level Dual-Cross Patterns for Robust Face Recognition

1 code implementation21 Jan 2014 Changxing Ding, Jonghyun Choi, DaCheng Tao, Larry S. Davis

To perform unconstrained face recognition robust to variations in illumination, pose and expression, this paper presents a new scheme to extract "Multi-Directional Multi-Level Dual-Cross Patterns" (MDML-DCPs) from face images.

Face Identification Face Recognition +2

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