Qihang Yu

I am a Research Scientist at ByteDance / TikTok. Previously, I received my Ph.D. degree from Computer Science department at Johns Hopkins University, advised by Bloomberg Distinguished Professor Dr. Alan Yuille. I am a member of Computational Cognition, Vision, and Learning.

Before that, I obtained B.S. in Computer Science at Peking University in 2018.

Email  /  Google Scholar

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News
  • 1 paper accepted to ECCV 2024
  • 2 paper accepted to CVPR 2024
  • 2 paper accepted to NeurIPS 2023
  • 1 paper accepted to WACV 2024 as Oral
  • 1 paper accepted to ICCV 2023
  • 1 paper accepted to CVPR 2023
  • 1 paper accepted to ICLR 2023
  • 2 paper accepted to ECCV 2022
  • 2 paper accepted to CVPR 2022, with one as Oral
Research

My research lies in generative modeling, multi-modality, and machine perception. For full list of my publications, please refer to my Google Scholar.

An Image is Worth 32 Tokens for Reconstruction and Generation
Qihang Yu*, Mark Weber*, Xueqing Deng, Xiaohui Shen, Daniel Cremers, Liang-Chieh Chen
Tech report, arXiv

Convolutions Die Hard: Open-Vocabulary Segmentation with Single Frozen Convolutional CLIP
Qihang Yu, Ju He, Xueqing Deng, Xiaohui Shen, Liang-Chieh Chen
NeurIPS, 2023

ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation
Shuyang Sun, Weijun Wang, Qihang Yu, Andrew Howard, Philip Torr, Liang-Chieh Chen
NeurIPS, 2023

Towards a Single Unified Model for Effective Detection, Segmentation, and Diagnosis of Eight Major Cancers Using a Large Collection of CT Scans
Jieneng Chen, Yingda Xia, Jiawen Yao, Ke Yan, Jianpeng Zhang, Le Lu, Fakai Wang, Bo Zhou, Mingyan Qiu, Qihang Yu, Mingze Yuan, Wei Fang, Yuxing Tang, Minfeng Xu, Jian Zhou, Yuqian Zhao, Qifeng Wang, Xianghua Ye, Xiaoli Yin, Yu Shi, Xin Chen, Jingren Zhou, Alan Yuille, Zaiyi Liu, Ling Zhang
ICCV, 2023

Video-kMaX: A Simple Unified Approach for Online and Near-Online Video Panoptic Segmentation
Inkyu Shin, Dahun Kim, Qihang Yu, Jun Xie, Hong-Seok Kim, Bradley Green, In So Kweon, Kuk-Jin Yoon, Liang-Chieh Chen
WACV, 2024 Oral

A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision
Lucas Beyer, Bo Wan, Gagan Madan, Filip Pavetic, Andreas Steiner, Alexander Kolesnikov, Andre Susano Pinto, Emanuele Bugliarello, Xiao Wang, Qihang Yu, Liang-Chieh Chen, Xiaohua Zhai
Tech report, arXiv

Compositor: Bottom-up Clustering and Compositing for Robust Part and Object Segmentation
Ju He, Jieneng Chen, Ming-Xian Lin, Qihang Yu, Alan Yuille
CVPR, 2023

MOAT: Alternating Mobile Convolution and Attention Brings Strong Vision Models
Chenglin Yang, Siyuan Qiao, Qihang Yu, Xiaoding Yuan, Yukun Zhu, Alan Yuille, Hartwig Adam, Liang-Chieh Chen
ICLR, 2023

k-means Mask Transformer
Qihang Yu, Huiyu Wang, Siyuan Qiao, Maxwell Collins, Yukun Zhu, Hartwig Adam, Alan Yuille, Liang-Chieh Chen
ECCV, 2022

PartImageNet: A Large, High-Quality Dataset of Parts
Ju He, Shuo Yang, Shaokang Yang, Adam Kortylewski, Xiaoding Yuan, Jie-Neng Chen, Shuai Liu, Cheng Yang, Qihang Yu, Alan Yuille
ECCV, 2022

CMT-DeepLab: Clustering Mask Transformers for Panoptic Segmentation
Qihang Yu, Huiyu Wang, Dahun Kim, Siyuan Qiao, Maxwell Collins, Yukun Zhu, Hartwig Adam, Alan Yuille, Liang-Chieh Chen
CVPR, 2022 Oral

TubeFormer-DeepLab: Video Mask Transformer
Dahun Kim, Jun Xie, Huiyu Wang, Siyuan Qiao, Qihang Yu, Hong-Seok Kim, Hartwig Adam, In So Kweon, Liang-Chieh Chen
CVPR, 2022

Glance-and-Gaze Vision Transformer
Qihang Yu, Yingda Xia, Yutong Bai, Yongyi Lu, Alan Yuille, Wei Shen
NeurIPS, 2021

DeepLab2: A TensorFlow Library for Deep Labeling
Mark Weber*, Huiyu Wang*, Siyuan Qiao*, Jun Xie, Maxwell D. Collins, Yukun Zhu, Liangzhe Yuan, Dahun Kim, Qihang Yu, Daniel Cremers, Laura Leal-Taixe, Alan L. Yuille, Florian Schroff, Hartwig Adam, Liang-Chieh Chen
Tech report, arXiv

Mask Guided Matting via Progressive Refinement Network
Qihang Yu, Jianming Zhang, He Zhang, Yilin Wang, Zhe Lin, Ning Xu, Yutong Bai, Alan Yuille
CVPR, 2021

TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation
Jieneng Chen, Yongyi Lu, Qihang Yu, Xiangde Luo, Ehsan Adeli, Yan Wang, Le Lu, Alan Yuille, Yuyin Zhou
Tech report, arXiv

Shape-Texture Debiased Neural Network Training
Yingwei Li, Qihang Yu, Mingxing Tan, Jieru Mei, Peng Tang, Wei Shen, Alan Yuille, Cihang Xie
ICLR, 2021

CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D Network
Qihang Yu, Yingwei Li, Jieru Mei, Yuyin Zhou, Alan Yuille
AAAI, 2021

Can Temporal Information Help with Contrastive Self-Supervised Learning?
Yutong Bai, Haoqi Fan, Ishan Misra, Ganesh Venkatesh, Yongyi Lu, Yuyin Zhou, Qihang Yu, Vikas Chandra, Alan Yuille
Tech report, arXiv

Detecting Pancreatic Adenocarcinoma in Multi-phase CT Scans via Alignment Ensemble
Yingda Xia, Qihang Yu, Wei Shen, Yuyin Zhou, Elliot K Fishman, Alan Yuille
MICCAI, 2020

C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation
Qihang Yu, Dong Yang, Holger Roth, Yutong Bai, Yixiao Zhang, Alan Yuille, Daguang Xu
CVPR, 2020

Neural Architecture Search for Lightweight Non-Local Networks
Yingwei Li, Xiaojie Jin, Jieru Mei, Xiaochen Lian, Linjie Yang, Cihang Xie, Qihang Yu, Yuyin Zhou, Song Bai, Alan Yuille
CVPR, 2020

When Radiology Report Generation Meets Knowledge Graph
Yixiao Zhang, Xiaosong Wang, Ziyue Xu, Qihang Yu, Alan Yuille, Daguang Xu
AAAI, 2020

Recurrent Saliency Transformation Network for Tiny Target Segmentation in Abdominal CT Scans
Lingxi Xie, Qihang Yu, Yuyin Zhou, Yan Wang, Elliot K Fishman, Alan Yuille
IEEE Transactions on Medical Imaging (TMI), 2019

Thickened 2D Networks for Efficient 3D Medical Image Segmentation
Qihang Yu, Yingda Xia, Lingxi Xie, Elliot K Fishman, Alan Yuille
Tech report, arxiv

Recurrent Saliency Transformation Network: Incorporating Multi-Stage Visual Cues for Small Organ Segmentation
Qihang Yu, Lingxi Xie, Yan Wang, Yuyin Zhou, Elliot K Fishman, Alan Yuille
CVPR, 2018


Stolen from Jon Barron