I am an incoming assistant professor at Texas A&M University in the CSE department, where I lead the Computer Vision Lab. I am a postdoctoral fellow at the Robotics Institute, CMU, working with Deva Ramanan. I received a Ph.D. from UC-Irvine, where I worked with Charless Fowlkes.
My research interests span Computer Vision and applied Machine Learning (CV/ML), and their applications to autonomous vehicles and research in natural science. My current research in CV/ML focuses on Visual Perception via Learning in the Open World (VPLOW). My recent paper on this topic was recognized for Best Paper / Marr Prize at ICCV 2021. I also actively apply my algorithms to interdisciplinary research including building a high-throughput pollen analysis system, which was featured by the National Science Foundation as that “opens a new era of fossil pollen research”.
I am looking for self-motivated PhD students starting Spring/Fall 2023 from CSE department, TAMU. PhD students will be fully funded with fellowships. Please feel free to contact me if interested.
contact
- gmail: aimerykong [at] gmail [dot] com
- email: shu [at] tamu [dot] edu
Links
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The 2nd Workshop on Dealing with Novelty in Open Worlds (DNOW) at WACV'23
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The 1st Workshop on Dealing with Novelty in Open Worlds (DNOW) at WACV'22
Teaching
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CSCE689: Visual Learning for Visual Recognition (Spring 2023).
Research Updates
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Congratulations to Samia on the WACV'23
paper "Creating a Forensic Database of Shoeprints from Online Shoe Tread Photos"! (10/10/2022)
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Congratulations to Shubham and Jeet on the WACV'23
paper "Far3Det: Towards Far-Field 3D Detection"! (10/10/2022)
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Congratulations to Zhiqiu on the NeurIPS'22
paper "Continual Learning With an Evolving Class Ontology"! Read more in the webstie. (9/14/2022)
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Congratulations to Neehar on the CoRL'22
paper "Towards Long Tailed 3D Detection"! (9/10/2022)
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Our 2nd workshop of Dealing with the Novelty in Open Worlds will be held on Jan 3rd, 2023, at WACV'23
in Waikoloa, Hawaii!
(8/15/2021)
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Congratulations to Yi-Ting, Jinghao, and Zelin on the ECCV'22
paper "Multimodal Object Detection via Probabilistic Ensembling",
which is accepted for oral presentation!
The proposed method was ranked the first in the KAIST challenge leaderboard.
Code is available in github. (7/8/2022)
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Our paper "OpenGAN: Open-Set Recognition Via Open Data Generation" has been published by IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) (6/18/2022)
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Our paper "Automated identification of diverse Neotropical pollen samples using convolutional neural networks" has been published by Methods in Ecology and Evolution (6/12/2022)
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Our workshop "Visual Perception and Learning in an Open World"
will be held in conjunction with CVPR'22
(4/29/2022)
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Congratulations to Shaden on the CVPR'22
paper "Long-Tailed Recognition via Weight Balancing"!
Code is available in the github page!
(3/2/2022)
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Our paper "OpenGAN: Open-Set Recognition via Open Data Generation" received honorable mention for Best Paper / Marr Prize at ICCV'21
.
Watch this 12min video
(10/12/2021) -
Our in-person workshop Dealing with the Novelty in Open Worlds will be held on Jan 4, 2022, in conjunction with WACV'22
(8/27/2021)
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Our challenge Open-World Image Classification
is online now! The challenge will be held in conjunction with
our Open World Vision workshop and CVPR'21 
(5/14/2021)
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Congratulations to Yunhan Zhao on the paper "Camera Pose Matters: Improving Depth Prediction by Mitigating Pose Distribution Bias", which is accepted for oral presentation by CVPR'21
(03/3/2021) -
Our virtual workshop Open-World Vision
will be held in conjunction with
CVPR'21
(12/11/2020)
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Our work is published on
"Improving the Taxonomy of Fossil Pollen using Convolutional Neural Networks and Superresolution Microscopy",
and featured by the NSF
.
(09/14/2020)