Tao Wang

I am a fourth-year Ph.D. student at National University of Singapore, generously supported by the Institue of Data Science scholarship, advised by Dr. Feng Jiashi, and Dr. Wang Xinchao. I was externally supervised by Prof. Yan Shuicheng during 2020-2021. Prior to Ph.D., I obtained my bachelor degree from Yingcai Honors College (elite school, candidates selected from top 5% undergraduates), University of Electronic Science and Technology of China.


Email address:   twangnh[dot]ai[at]gmail[dot]com

Other links:  Google Scholar, GitHub

Research Statement

I'm developing Machine Learning approaches for visual perception in the open world. The major focus is designing effective methods to handle practical challenges in real-world non-ideal environments. Specifically,  I'm taking two perspectives: 1) Handle open-world data that may be long-tailed, biased, unlabeled, or contains unknown, anomaly concepts. 2) Develop efficient learning and inference methods to gain superior training data efficiency and runtime efficiency, these include knowledge distillation, X-shot & Y-supervised learning, domain adaptation, and network architecture design.

Research Interests

My current interest spans object and human recognition, detection, and segmentation, with the following topics:

long-tailed/imbalanced data, biased data, unlabeled data, high-resolution data, multi-modal data

knowledge distillation, open-vocabulary/set recognition, domain adaptation, self/weakly-supervised learning

     transformers for instance-level understanding, network design for mobile applications

I'm always open to research collaboration and discussion, please feel free to contact me!

News

Featured Works [Full List]

Open-world Data: Long-tailed Distribution

Learning Box Regression and Mask Segmentation under Long-tailed Distribution with

Gradient Transfusing (CRAT)


Tao Wang, Li Yuan, Jiashi Feng and Xinchao Wang,


Preprint 2022, Under review at IJCV Special Issue for Robust Vision, Code will come soon

Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax

Yu Li, Tao Wang, Bingyi Kang, Sheng Tang, Chunfeng Wang, Jintao Li, Jiashi Feng

CVPR 2020 Oral, [Paper][Code][Video]


The Devil is in Classification: A Simple Framework for Long-tail Instance Segmentation (SimCal)

Tao Wang, Yu Li, Bingyi Kang, Junnan Li, Junhao Liew, Sheng Tang, Steven Hoi, and Jiashi Feng

ECCV 2020, [Paper][Code][Video]

Joint COCO and Mapillary Workshop at ICCV 2019: LVIS Challenge Track: Classification Calibration for Long-tail Instance Segmentation

Tao Wang, Yu Li, Bingyi Kang, Junnan Li, Junhao Liew, Sheng Tang, Steven Hoi, Jiashi Feng

Winner solution for the 1st LVIS challenge at ICCV 2019 [Tech Report]

Efficient Learning Methods

Learning to Detect and Segment for Open Vocabulary Object Detection (CondHead) 

Tao Wang, Nan Li

Preprint 2022, Under review at CVPR 2023, Code will come soon

PoseTriplet: Co-evolving 3D Human Pose Estimation, Imitation, and Hallucination under Self-supervision

Kehong Gong*, Bingbing Li*, Jianfeng Zhang*, Tao Wang*, Jing Huang, Michael Bi Mi, Jiashi Feng, Xinchao Wang (* equal contribution)

CVPR 2022 Oral, [Paper][Code][Video]

Revisiting Knowledge Distillation via Label Smoothing Regularization

Li Yuan, Francis EH Tay, Guilin Li, Tao Wang, Jiashi Feng

CVPR 2020 Oral, [Paper][Code][Video]

Distilling Object Detectors with Fine-grained Feature Imitation

Tao Wang, Li Yuan, Xiaopeng Zhang, Jiashi Feng

CVPR 2019, [Paper][Code]

Few-shot Adaptive Faster R-CNN

Tao Wang, Xiaopeng Zhang, Li Yuan, Jiashi Feng

CVPR 2019, [Paper][Code]

Network Architecture Design

SODAR: Segmenting Objects by Dynamically Aggregating Neighboring Mask Representations

Tao Wang, Jun Hao Liew, Yu Li, Yunpeng Chen, Jiashi Feng

TIP 2022, [Paper][Code]

Detect Multi-person with 3D Pose Directly from Multi-view images (Multi-view Pose Transformer, MvP)

Tao Wang, Jianfeng Zhang, Yujun Cai, Shuicheng Yan, Jiashi Feng

NeurIPS 2021, [Paper][Code][Industrial Recognition by XRMoCap][Video][Slides]

Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet

Li Yuan*, Yunpeng Chen, Tao Wang*, Weihao Yu, Yujun Shi, Zihang Jiang, Francis E.H. Tay, Jiashi Feng, Shuicheng Yan (Work done during internship at Yitu)

ICCV 2021, [Paper][Code][Video][Most Influential ICCV Papers]

PnP-DETR: Towards Efficient Visual Analysis with Transformers

Tao Wang, Li Yuan, Yunpeng Chen, Jiashi Feng, Shuicheng Yan

ICCV 2021, [Paper][Code][Video]

Academic Activities

Competitions:

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Work Experience

Teaching