Please also see my publications at Google
Scholar.
When Is Multilinguality a Curse? Language
Modeling for 250 High-and Low-Resource Languages Tyler A Chang, Catherine Arnett, Zhuowen Tu, and Benjamin K Bergen EMNLP 2024 / Paper |
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Dolfin: Diffusion Layout Transformers
without Autoencoder Yilin Wang, Zeyuan Chen, Liangjun Zhong, Zheng Ding, Zhizhou Sha, and Zhuowen Tu ECCV 2024 / Paper |
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Open-World
Dynamic Prompt and Continual Visual Representation Learning Youngeun Kim, Jun Fang, Qin Zhang, Zhaowei Cai, Yantao Shen, Rahul Duggal, Dripta S. Raychaudhuri, Zhuowen Tu, Yifan Xing, and Onkar Dabeer ECCV 2024 / Paper |
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Bayesian Diffusion Models for 3D Shape
Reconstruction Haiyang Xu*, Yu Lei*, Zeyuan Chen, Xiang Zhang, Yue Zhao, Yilin Wang, and Zhuowen Tu (*equal contribution) CVPR 2024 / Paper |
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TokenCompose: Grounding Diffusion with Token-level Supervision Zirui Wang, Zhizhou Sha, Zheng Ding, Yilin Wang, Zhuowen Tu CVPR 2024 / Paper / Project Page |
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HOIDiffusion: Generating Realistic 3D Hand-Object Interaction Data Mengqi Zhang, Yang Fu, Zheng Ding, Sifei Liu, Zhuowen Tu, Xiaolong Wang CVPR 2024 / Paper / Project Page |
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Restoration by Generation with Constrained Priors Zheng Ding, Xuaner Zhang, Zhuowen Tu, Zhihao Xia CVPR 2024 / Paper / Project Page |
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Non-autoregressive Sequence-to-Sequence
Vision-Language Models Kunyu Shi, Qi Dong, Luis Goncalves, Zhuowen Tu, Stefano Soatto CVPR 2024 / Paper |
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Enhancing Vision-Language Pre-training with Rich Supervisions Yuan Gao, Kunyu Shi, Pengkai Zhu, Edouard Belval, Oren Nuriel, Srikar Appalaraju, Shabnam Ghadar, Vijay Mahadevan, Zhuowen Tu, Stefano Soatto CVPR 2024 / Paper |
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On the Scalability of Diffusion-based
Text-to-Image Generation Hao Li, Yang Zou, Ying Wang, Orchid Majumder, Yusheng Xie, R. Manmatha, Ashwin Swaminathan, Zhuowen Tu, Stefano Ermon, Stefano Soatto CVPR 2024 / Paper |
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Patched Denoising Diffusion Models For High-Resolution Image Synthesis Zheng Ding*, Mengqi Zhang*, Jiajun Wu, and Zhuowen Tu (*equal contribution) ICLR 2024 / Paper / Project Page |
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BLIVA: A Simple Multimodal LLM for Better Handling of Text-Rich Visual Questions Wenbo Hu*, Yifan Xu*, Yi Li, Weiyue Li, Zeyuan Chen, Zhuowen Tu (*equal contribution) AAAI 2024 / Paper |
Uni-3D: A Universal Model for Panoptic 3D Scene Reconstruction Xiang Zhang*, Zeyuan Chen*, Fangyin Wei, and Zhuowen Tu (*equal contribution) ICCV 2023 / Paper |
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MasQCLIP for Open-Vocabulary Universal Image Segmentation Xin Xu*, Tianyi Xiong*, Zheng Ding, and Zhuowen Tu (*equal contribution) ICCV 2023 / Paper |
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Single-Stage Diffusion NeRF: A Unified Approach to 3D Generation and Reconstruction Hansheng Chen, Jiatao Gu, Anpei Chen, Wei Tian, Zhuowen Tu, Lingjie Liu, Hao Su ICCV 2023 / Paper |
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Distilling Large Vision-Language Model with Out-of-Distribution Generalizability Xuanlin Li, Yunhao Fang, Minghua Liu, Zhan Ling, Zhuowen Tu, Hao Su ICCV 2023 / Paper |
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DocTr: Document Transformer for Structured Information Extraction in Documents Haofu Liao, Aruni RoyChowdhury, Weijian Li, Ankan Bansal, Yuting Zhang, Zhuowen Tu, Ravi Kumar Satzoda, R Manmatha, Vijay Mahadevan ICCV 2023 / Paper |
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Object-centric Multiple Object Tracking Zixu Zhao, Jiaze Wang, Max Horn, Yizhuo Ding, Tong He, Zechen Bai, Dominik Zietlow, Carl-Johann Simon-Gabriel, Bing Shuai, Zhuowen Tu, Thomas Brox, Bernt Schiele, Yanwei Fu, Francesco Locatello, Zheng Zhang, Tianjun Xiao ICCV 2023 / Paper |
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SkeleTR: Towards Skeleton-based Action Recognition in the Wild Haodong Duan, Mingze Xu, Bing Shuai, Davide Modolo, Zhuowen Tu, Joseph Tighe, Alessandro Bergamo ICCV 2023 / Paper |
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Open-Vocabulary Universal Image Segmentation with MaskCLIP Zheng Ding, Jieke Wang, and Zhuowen Tu ICML 2023 / Paper |
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DiffusionRig: Learning Personalized Priors for Facial Appearance Editing Zheng Ding, Xuaner Zhang, Zhihao Xia, Lars Jebe, Zhuowen Tu, and Xiuming Zhang CVPR 2023 / Paper |
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Guided Recommendation for Model Fine-Tuning Hao Li, Charless Fowlkes, Hao Yang, Onkar Debeer, Zhuowen Tu, and Stefano Soatto CVPR 2023 / Paper |
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On the Feasibility of Cross-Task Transfer
with Model-Based Reinforcement Learning Yifan Xu*, Nicklas Hansen*, Zirui Wang, Yung-Chieh Chan, Hao Su, and Zhuowen Tu (*equal contribution) ICLR 2023 / Paper |
Semi-supervised Vision Transformers at Scale Zhaowei Cai, Avinash Ravichandran, Paolo Favaro, Manchen Wang, Davide Modolo, Rahul Bhotika, Zhuowen Tu, and Stefano Soatto NeurIPS 2022 / Paper |
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An In-depth Study of Stochastic
Backpropagation Jun Fang, Mingze Xu, Hao Chen, Bing Shuai, Zhuowen Tu, and Joseph Tighe NeurIPS 2022 / Paper |
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The Geometry of Multilingual Language Model
Representations Tyler A. Chang, Zhuowen Tu, and Benjamin K. Bergen EMNLP 2022 / Paper |
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X-DETR: A Versatile Architecture for
Instance-wise Vision-Language Tasks Zhaowei Cai, Gukyeong Kwon, Avinash Ravichandran, Erhan Bas, Zhuowen Tu, Rahul Bhotika, and Stefano Soatta ECCV 2022 / Paper |
Text Spotting Transformers Xiang Zhang, Yongwen Su, Subarna Tripathi, and Zhuowen Tu CVPR 2022 / Paper / Code |
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Instance Segmentation with Mask-supervised
Polygonal Regression Transformers Justin Lazarow, Weijian Xu, and Zhuowen Tu CVPR 2022 / Paper / Code |
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MeMOT: Multi-Object Tracking with Memory Jiarui Cai, Wei Li, Mingze Xu, Yuanjun Xiong, Wei Xia, Zhuowen Tu, and Stefano Soatto CVPR 2022 / Paper Oral Presentation |
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ViTGAN: Training GANs with
Vision Transformers Kwonjoon Lee, Huiwen Chang, Lu Jiang, Han Zhang, Zhuowen Tu, and Ce Liu ICLR 2022 / Paper / Code Spotlight |
Long
Short-Term Transformer for Online Action Detection Mingze Xu, Yuanjun Xiong, Hao Chen, Xinyu Li, Wei Xia, Zhuowen Tu, Stefano Soatto NeurIPS 2021 / Paper / Code Spotlight |
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Co-Scale Conv-Attentional Image Transformers Weijian Xu*, Yifan Xu*, Tyler A. Chang, and Zhuowen Tu (*equal contribution) ICCV 2021 / Paper / Code Oral Presentation |
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Visual Relationship Detection Using
Part-and-Sum Transformers with Composite Queries Qi Dong, Zhuowen Tu, Haofu Liao, Yuting Zhang, Vijay Mahadevan, Stefano Soatto ICCV 2021 / Paper |
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Convolutions
and Self-Attention: Re-interpreting Relative Positions in Pre-trained
Language Models Tyler A. Chang, Yifan Xu, Weijian Xu, and Zhuowen Tu ACL 2021 / Paper (long) / Code |
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Line Segment Detection Using Transformers
without Edges Yifan Xu*, Weijian Xu*, David Cheung, and Zhuowen Tu (*equal contribution) CVPR 2021 / Paper / Code Oral Presentation |
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Dual Contradistinctive
Generative
Autoencoder Gaurav Parmar*, Dacheng Li*, Kwonjoon Lee*, and Zhuowen Tu (*equal contribution) CVPR 2021 / Paper / Code |
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Pose Recognition with
Cascade Transformers Ke Li*, Shijie Wang*, Xiang Zhang*, Yifan Xu, Weijian Xu, and Zhuowen Tu (*equal contribution) CVPR 2021 / Paper / Code |
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Exponential Moving Average
Normalization
for Self-supervised and Semi-supervised Learning Zhaowei Cai, Avinash Ravichandran, Subhransu Maji, Charless Fowlkes, Zhuowen Tu, and Stefano Soatto CVPR 2021 / Paper Oral Presentation |
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Compatibility-aware
Heterogeneous Visual
Search Rahul Duggal, Hao Zhou, Shuo Yang, Yuanjun Xiong, Wei Xia, Zhuowen Tu, and Stefano Soatto CVPR 2021 / Paper |
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Attentional Constellation
Nets for Few-Shot
Learning Weijian Xu*, Yifan Xu*, Huaijin Wang*, and Zhuowen Tu (*equal contribution) ICLR 2021 / Paper |
One-Pixel Signature: Characterizing CNN
Models for Backdoor Detection Shanjiaoyang Huang*, Weiqi Peng*, Zhiwei Jia, and Zhuowen Tu (*equal contribution) ECCV 2020 / Paper |
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Recognizing Objects from
Any View with
Object and Viewer-Centered Representations Sainan Liu, Vincent Nguyen, Isaac Rehg, and Zhuowen Tu CVPR 2020 / Paper |
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Learning Instance Occlusion
for Panoptic
Segmentation Justin Lazarow*, Kwonjoon Lee*, Kunyu Shi*, and Zhuowen Tu (*equal contribution) CVPR 2020 / Paper / Code |
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Guided Variational
Autoencoder for
Disentanglement Learning Zheng Ding*, Yifan Xu*, Weijian Xu, Gaurav Parmar, Yang Yang, Max Welling, and Zhuowen Tu (*equal contribution) CVPR 2020 / Paper |
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Topology-Aware Single-Image
3D Shape
Reconstruction Qimin Chen, Vincent Nguyen, Feng Han, Raimondas Kiveris, and Zhuowen Tu CVPR 2020 Workshop on Learning 3D Generative Models / Paper |
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Local Binary Pattern
Networks Jeng-Hau Lin, Justin Lazarow, Yunfan Yang, Dezhi Hong, Rajesh Gupta, and Zhuowen Tu WACV 2020 / Paper |
Learning Geometry-aware
Skeleton
Detection Weijian Xu, Gaurav Parmar, and Zhuowen Tu BMVC 2019 / Paper |
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3D
Volumetric Modeling with Introspective Neural Networks Wenlong Huang*, Brian Lai*, Weijian Xu, and Zhuowen Tu (*equal contribution) AAAI 2019 / Paper |
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Accelerating
Local Binary Pattern Networks
with Software-Programmable FPGAs Jeng-Hau Lin, Atieh Lotfi, Vahideh Akhlaghi, Zhuowen Tu, and Rajesh Gupta Desgin, Automation and Test in Europe (DATE) 2019 / Paper |
Rethinking Spatiotemporal
Feature Learning:
Speed-Accuracy Trade-offs in Video Classification Saining Xie, Chen Sun, Jonathan Huang, Zhuowen Tu, and Kevin Murphy ECCV 2018 / Paper |
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Wasserstein Introspective
Neural Networks Kwonjoon Lee, Weijian Xu, Fan Fan, and Zhuowen Tu CVPR 2018 / Paper / Code Oral Presentation |
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Attentional ShapeContextNet
for Point Cloud
Recognition Saining Xie*, Sainan Liu*, Zeyu Chen, and Zhuowen Tu (*equal contribution) CVPR 2018 / Paper / Code |
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Deep Convolutional Neural
Networks with
Merge-and-Run Mappings Liming Zhao, Mingjie Li, Depu Meng, Xi Li, Zhaoxiang Zhang, Yueting Zhuang, Zhuowen Tu, and Jingdong Wang IJCAI 2018 / Pape r / Code |
Introspective Classification with
Convolutional Nets Long Jin, Justin Lazarow, and Zhuowen Tu NeurIPS 2017 / Paper / Code |
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Introspective
Neural
Networks for
Generative Modeling Justin Lazarow*, Long Jin*, and Zhuowen Tu (*equal contribution) ICCV 2017 / Paper / Code |
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Aggregated Residual
Transformations for
Deep Neural Networks Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He CVPR 2017 / Paper / Code |
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Deeply Supervised Salient
Object Detection
with Short Connections Qibin Hou, Ming-Ming Cheng, Xiao-Wei Hu, Ali Borji, Zhuowen Tu, and Philip Torr CVPR 2017 / Paper / Code |
Top-down Learning for
Structured Labeling
with Convolutional Pseudoprior Saining Xie*, Xun Huang*, and Zhuowen Tu (*equal contribution) ECCV 2016 / Paper |
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HFS:
Hierarchical Feature
Selection for
Efficient Image Segmentation Ming-Ming Cheng, Yun Liu, Qibin Hou, Jiawang Bian, Philip Torr, Shimin Hu, and Zhuowen Tu ECCV 2016 / Paper / Code |
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Dense Volume-to-Volume
Vascular Boundary
Detection Jameson Merkow, David Kriegman, Alison Marsden, and Zhuowen Tu MICCAI 2016 / Paper |
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Generalizing Pooling Functions in
Convolutional Neural Networks: Mixed, Gated, and Tree Chen-Yu Lee, Patrick Gallagher, and Zhuowen Tu AISTATS 2016 / Paper / Code |
Holistically-Nested Edge
Detection Saining Xie and Zhuowen Tu ICCV 2015 / Paper / Code / IJCV Version Marr Prize Honorable Mention |
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Deeply-Supervised
Nets
Chen-Yu Lee*, Saining Xie*, Patrick Gallagher, Zhengyou Zhang, and Zhuowen Tu (*equal contribution) AISTATS 2015 / Paper / Code / arXiv Oral Presentation at the NeurIPS'14 Deep Learning Workshop |
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Structural Edge Detection
for
Cardiovascular Modeling Jameson Merkow, Zhuowen Tu, David Kriegman, Alison Marsden MICCAI 2016 / Paper |