Cihang Xie

I am an Assistant Professor of Computer Science and Engineering at University of California, Santa Cruz. My research interest lies at the intersection of computer vision and machine learning, with the goal of building human-level computer vision systems. I am particularly interested in securing model performance under distribution shifts, and developing deep representation learning with minimal supervision.

I received my Ph.D. degree from Johns Hopkins University, advised by Bloomberg Distinguished Professor Alan Yuille. I have worked as a research intern with Kaiming He and Laurens van der Maaten at the Facebook AI Research (FAIR); Quoc Le at the Google Brain. I receive the 2020 Facebook Fellowship.


           

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Hiring: I am co-leading the Vision · Learning · Assured Autonomy (VLAA) Lab with Professor Yuyin Zhou. Our lab has multiple openings for summer interns and visiting students with flexible starting times. If you are interested in these opportunities, please complete this form.


Recent News
  • [NEW] We release Recap-DataComp-1B, where we use a LLaMA-3-powered LLaVA model to recaption the entire 1.3 billion images from DataComp-1B. Our Recap-DataComp-1B shows higher textual quality, and can help to train stronger CLIP models and T2I models.
  • [July 2024] Three papers are accepted by ECCV 2024.
  • [May 2024] Congratulations to Xianhang Li on winning the Jack Baskin & Peggy Downes-Baskin Fellowship. Additionally, D-iGPT is accepted by ICML 2024 --- our strongest model secures an ImageNet top-1 accuracy of 90.0% with ViT-H.
  • [April 2024] We release HQ-Edit, a dataset with high-resolution images & detailed and aligned editing instructions. Our fine-tuned InstructPix2Pix delivers superior editing performance. Additionally, two papers are accepted by TMLR.
  • [March 2024] One paper is accepted by NAACL 2024, and one paper is accepted by TMLR.
  • [February 2024] Three papers (AdvXL, MixCon3D, L2B) are accepted by CVPR 2024.
  • [January 2024] Our Tuning LayerNorm in Attention is accepted by ICLR 2024 as a spotlight paper; our visual probing is accpted by EACL 2024.
  • [NEW] Congratulations to Zijun and the team on winning the 2nd place in both the base model subtrack and the large model subtrack, Red Teaming Track, in NeurIPS 2023 Trojan Detection Challenge. We will release the code and the report soon.
  • [December 2023] One paper is accepted by TMLR. Additionally, we release D-iGPT, which attains 89.5% ImageNet top-1 accuracy with ViT-L. Larger models are coming!
  • [November 2023] CLIPA-v2 is accepted by NeurIPS 2023 R0-FoMo Workshop, and Sight Beyond Text is accepted by NeurIPS 2023 Instruction Workshop.
  • [October 2023] Congratulations to Siwei and the team on winning the 2nd place in Task 4: Brain Metastases Segmentation of MICCAI 2023 BraTS Challenge.
  • [September 2023] CLIPA is accepted by NeurIPS 2023. In addition, we release our best model, CLIPA-G/14, which attains 83.0% zero-shot ImageNet top-1 accuracy.
  • [NEW] We release CLIPA, which enables CLIP training with limited computational resources. Furthermore, at a low cost of just $15,000, our CLIPA-v2 effectively elevates the zero-shot ImageNet top-1 accuracy to an impressive 81.8%.
  • [July 2023] Three papers are accepted by ICCV 2023.
  • [June 2023] Two papers are accepted by MICCAI 2023.
  • [February 2023] DMAE is accepted by CVPR 2023.
  • [January 2023] Two papers are accepted by ICLR 2023.
  • I am serving as an Area Chair for CVPR 2024/2023, ICLR 2024/2023/2022, ICML 2024/2023, ICCV 2023/2021, NeurIPS 2024/2023/2022, ECCV 2022, and a Senior Program Committee for AAAI 2022, IJCAI 2021.

Current Students
  • Xianhang Li (Ph.D. of 2021, UC Santa Cruz Chancellor's Fellowship, Jack Baskin & Peggy Downes-Baskin Fellowship)
  • Zeyu Wang (Ph.D. of 2021)
  • Siwei Yang (Ph.D. of 2023)
  • Mude Hui (Ph.D. of 2023, co-supervised with Yuyin Zhou)
  • Jinrui Yang (Ph.D. of 2023, co-supervised with Yuyin Zhou)
  • Zijun Wang (Ph.D. of 2024)
  • Yanqing Liu (Ph.D. of 2024)
  • Haoqin Tu (Ph.D. of 2024, UC Santa Cruz Chancellor's Fellowship Recipient, co-supervised with Yuyin Zhou)
  • Xiaoke Huang (Ph.D. of 2024, co-supervised with Yuyin Zhou)
  • Juncheng Wu (Ph.D. of 2024, co-supervised with Yuyin Zhou)
  • Chen Wei (affiliated Ph.D. student from Johns Hopkins University)
  • Junfei Xiao (affiliated Ph.D. student from Johns Hopkins University)
  • Sucheng Ren (affiliated Ph.D. student from Johns Hopkins University)
  • Lei Zhang (affiliated Ph.D. student from UC San Diego)
  • Bingchen Zhao (visiting graduate student from University of Edinburgh)
  • Fangxun Shu (visiting graduate student in Summer'24)
  • Yunfei Xie (visiting undergraduate student in Summer'24)
Alumni
2023
  • Zijun Wang (visiting undergraduate student in Summer'23; next: Ph.D. at UC Santa Cruz)
  • Haoqin Tu (visiting graduate student in Summer'23; next: Ph.D. at UC Santa Cruz)
  • Lei Zhang (visiting graduate student in Summer'23; next: Ph.D. at UC San Diego)
  • Yipeng Gao (visiting graduate student in Summer'23; next: Ph.D. at University of Southern California)
  • Jieru Mei (affiliated Ph.D. student from Johns Hopkins University; next: Google)
  • Zhuowan Li (affiliated Ph.D. student from Johns Hopkins University; next: Google)
  • Yixiao Zhang (affiliated Ph.D. student from Johns Hopkins University; next: Amazon)
2022
  • Sizhe Chen (visiting graduate student in 2022; next: Ph.D. at UC Berkeley)
  • Yuanze Lin (visiting graduate student in Summer'22; next: Ph.D. at University of Oxford)
  • Chen Wang (visiting graduate student in Summer'22; next: Ph.D. at University of Pennsylvania)
  • Zihan Li (visiting graduate student in Summer'22; next: Ph.D. at University of Washington)
  • Junyang Wu (visiting undergraduate student in Summer'22; next: Ph.D. at Shanghai Jiao Tong University)
  • Shaoyuan Xie (visiting undergraduate student in Summer'22; next: Ph.D. at UC Irvine)
  • Yiqing Wang (visiting undergraduate student in Summer'22; next: Ph.D. at Duke University)
  • Peiran Xu (visiting undergraduate student in Summer'22; next: Ph.D. at UCLA)
  • Yunchao Zhang (visiting undergraduate student in Summer'22; next: Ph.D. at The University of Hong Kong)
  • Zihao Wei (visiting undergraduate student in Summer'22; next: Master at UMich)
2021
  • Sucheng Ren (visiting graduate student in Summer'21; next: Ph.D. at Johns Hopkins University)
  • Jinghao Zhou (visiting undergraduate student in Summer'21; next: Ph.D. at University of Oxford)
2020
  • Yingwei Li (affiliated Ph.D. student from Johns Hopkins University; next: Waymo)
  • Yucheng Han (visiting undergraduate student in Summer'20; next: Ph.D. at Nanyang Technological University)

Publications

2024

What If We Recaption Billions of Web Images with LLaMA-3?
Xianhang Li, Haoqin Tu, Mude Hui, Zeyu Wang, Bingchen Zhao, Junfei Xiao, Sucheng Ren, Jieru Mei, Qing Liu, Huangjie Zheng, Yuyin Zhou, Cihang Xie
arxiv, 2024


Rejuvenating image-GPT as Strong Visual Representation Learners
Sucheng Ren, Zeyu Wang, Hongru Zhu, Junfei Xiao, Alan Yuille, Cihang Xie
ICML, 2024


How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs
Haoqin Tu, Chenhang Cui, Zijun Wang, Yiyang Zhou, Bingchen Zhao, Junlin Han, Wangchunshu Zhou, Huaxiu Yao, Cihang Xie
ECCV, 2024


A Semantic Space is Worth 256 Language Descriptions: Make Stronger Segmentation Models with Descriptive Properties
Junfei Xiao, Ziqi Zhou, Wenxuan Li, Shiyi Lan, Jieru Mei, Zhiding Yu, Bingchen Zhao, Alan Yuille, Yuyin Zhou, Cihang Xie
ECCV, 2024


From Pixels to Objects: A Hierarchical Approach for Part and Object Segmentation Using Local and Global Aggregation
Yunfei Xie, Cihang Xie, Alan Yuille, Jieru Mei
ECCV, 2024


Autoregressive Pretraining with Mamba in Vision
Sucheng Ren, Xianhang Li, Haoqin Tu, Feng Wang, Fangxun Shu, Lei Zhang, Jieru Mei, Linjie Yang, Peng Wang, Heng Wang, Alan Yuille, Cihang Xie
arxiv, 2024


Mamba®: Vision Mamba ALSO Needs Registers
Feng Wang, Jiahao Wang, Sucheng Ren, Guoyizhe Wei, Jieru Mei, Wei Shao, Yuyin Zhou, Alan Yuille, Cihang Xie
arxiv, 2024


Scaling White-Box Transformers for Vision
Jinrui Yang, Xianhang Li, Druv Pai, Yuyin Zhou, Yi Ma, Yadong Yu, Cihang Xie
arxiv, 2024


HQ-Edit: A High-Quality Dataset for Instruction-based Image Editing
Mude Hui, Siwei Yang, Bingchen Zhao, Yichun Shi, Heng Wang, Peng Wang, Cihang Xie, Yuyin Zhou
arxiv, 2024


AQA-Bench: An Interactive Benchmark for Evaluating LLMs' Sequential Reasoning Ability
Siwei Yang, Bingchen Zhao, Cihang Xie
arxiv, 2024


ARVideo: Autoregressive Pretraining for Self-Supervised Video Representation Learning
Sucheng Ren, Hongru Zhu, Chen Wei, Yijiang Li, Alan Yuille, Cihang Xie
arxiv, 2024


Revisiting Adversarial Training at Scale
Zeyu Wang, Xianhang Li, Hongru Zhu, Cihang Xie
CVPR, 2024


Sculpting Holistic 3D Representation in Contrastive Language-Image-3D Pre-training
Yipeng Gao, Zeyu Wang, Wei-Shi Zheng, Cihang Xie, Yuyin Zhou
CVPR, 2024


Learning to Bootstrap for Combating Label Noise
Yuyin Zhou, Xianhang Li, Fengze Liu, Xuxi Chen, Lequan Yu, Cihang Xie, Matthew P. Lungren, Lei Xing
CVPR, 2024


Benchmarking Robustness in Neural Radiance Fields
Chen Wang, Angtian Wang, Junbo Li, Alan Yuille, Cihang Xie
CVPR Adversarial Machine Learning Workshop, 2024


Tuning LayerNorm in Attention: Towards Efficient MultiModal LLM Finetuning
Bingchen Zhao, Haoqin Tu, Chen Wei, Jieru Mei, Cihang Xie
ICLR, 2024


Navigation as the Attacker Wishes? Towards Building Byzantine-Robust Embodied Agents under Federated Learning
Yunchao Zhang, Zonglin Di, Kaiwen Zhou, Cihang Xie, Xin Eric Wang
NAACL, 2024


Localization vs. Semantics: Visual Representations in Unimodal and Multimodal Models
Zhuowan Li, Cihang Xie, Benjamin Van Durme, Alan Yuille
EACL, 2024


On the Adversarial Robustness of Camera-based 3D Object Detection
Shaoyuan Xie, Zichao Li, Zeyu Wang, Cihang Xie
TMLR, 2024


Unleashing the Power of Visual Prompting At the Pixel Level
Junyang Wu, Xianhang Li, Chen Wei, Huiyu Wang, Alan Yuille, Yuyin Zhou, Cihang Xie
TMLR, 2024


FedConv: Enhancing Convolutional Neural Networks for Handling Data Heterogeneity in Federated Learning
Peiran Xu, Zeyu Wang, Jieru Mei, Liangqiong Qu, Alan Yuille, Cihang Xie, Yuyin Zhou
TMLR, 2024


Scaling (Down) CLIP: A Comprehensive Analysis of Data, Architecture, and Training Strategies
Zichao Li, Cihang Xie, Ekin Dogus Cubuk
TMLR, 2024


SPFormer: Enhancing Vision Transformer with Superpixel Representation
Jieru Mei, Liang-Chieh Chen, Alan Yuille, Cihang Xie
arxiv, 2024


2023

Audio-Visual LLM for Video Understanding
Fangxun Shu, Lei Zhang, Hao Jiang, Cihang Xie
arxiv, 2023


Compress & Align: Curating Image-Text Data with Human Knowledge
Lei Zhang, Fangxun Shu, Sucheng Ren, Hao Jiang, Bingchen Zhao, Cihang Xie
arxiv, 2023


Sight Beyond Text: Multi-Modal Training Enhances LLMs in Truthfulness and Ethics
Haoqin Tu, Bingchen Zhao, Chen Wei, Cihang Xie
NeurIPS Instruction Workshop, 2023


CLIPA-v2: Scaling CLIP Training with 81.1% Zero-shot ImageNet Accuracy within a $10,000 Budget; An Extra $4,000 Unlocks 81.8% Accuracy
Xianhang Li, Zeyu Wang, Cihang Xie
NeurIPS R0-FoMo Workshop, 2023


An Inverse Scaling Law for CLIP Training
Xianhang Li, Zeyu Wang, Cihang Xie
NeurIPS, 2023


Diffusion Models as Masked Autoencoders
Chen Wei, Karttikeya Mangalam, Po-Yao Huang, Yanghao Li, Haoqi Fan, Hu Xu, Huiyu Wang, Cihang Xie, Alan Yuille, Christoph Feichtenhofer
ICCV, 2023


SMAUG: Sparse Masked Autoencoder for Efficient Video-Language Pre-training
Yuanze Lin, Chen Wei, Huiyu Wang, Alan Yuille, Cihang Xie
ICCV, 2023


DistillBEV: Boosting Multi-Camera 3D Object Detection with Cross-Modal Knowledge Distillation
Zeyu Wang, Dingwen Li, Chenxu Luo, Cihang Xie, Xiaodong Yang
ICCV, 2023


SwinMM: Masked Multi-view with Swin Transformers for 3D Medical Image Segmentation
Yiqing Wang, Zihan Li, Jieru Mei, Zihao Wei, Li Liu, Chen Wang, Shengtian Sang, Alan Yuille, Cihang Xie, Yuyin Zhou
MICCAI, 2023


Consistency-guided Meta-Learning for Bootstrapping Semi-Supervised Medical Image Segmentation
Qingyue Wei, Lequan Yu, Xianhang Li, Wei Shao, Cihang Xie, Lei Xing, Yuyin Zhou
MICCAI, 2023


Masked Autoencoders Enable Efficient Knowledge Distillers
Yutong Bai, Zeyu Wang, Junfei Xiao, Chen Wei, Huiyu Wang, Alan Yuille, Yuyin Zhou, Cihang Xie
CVPR, 2023


Can CNNs Be More Robust Than Transformers?
Zeyu Wang, Yutong Bai, Yuyin Zhou, Cihang Xie
ICLR, 2023


One-Pixel Shortcut: on the Learning Preference of Deep Neural Networks
Shutong Wu, Sizhe Chen, Cihang Xie, Xiaolin Huang
ICLR, 2023


BNET: Batch Normalization with Enhanced Linear Transformation
Yuhui Xu, Lingxi Xie, Cihang Xie, Wenrui Dai, Jieru Mei, Siyuan Qiao, Wei Shen, Hongkai Xiong, Alan Yuille
IEEE TPAMI, 2023


Practical Disruption of Image Translation Deepfake Networks
Nataniel Ruiz, Sarah Adel Bargal, Cihang Xie, Stan Sclaroff
AAAI, 2023


2022

Bag of Tricks for FGSM Adversarial Training
Zichao Li, Li Liu, Zeyu Wang, Yuyin Zhou, Cihang Xie
arxiv, 2022


Finding Differences Between Transformers and ConvNets Using Counterfactual Simulation Testing
Nataniel Ruiz, Sarah Adel Bargal, Cihang Xie, Kate Saenko, Stan Sclaroff
NeurIPS, 2022


Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks
Sizhe Chen, Zhehao Huang, Qinghua Tao, Yingwen Wu, Cihang Xie, Xiaolin Huang
NeurIPS, 2022


In Defense of Image Pre-Training for Spatiotemporal Recognition
Xianhang Li, Huiyu Wang, Chen Wei, Jieru Mei, Alan Yuille, Yuyin Zhou, Cihang Xie
ECCV, 2022


ViP: Unified Certified Detection and Recovery for Patch Attack with Vision Transformers
Junbo Li, Huan Zhang, Cihang Xie
ECCV, 2022


A Simple Data Mixing Prior for Improving Self-Supervised Learning
Sucheng Ren, Huiyu Wang, Zhengqi Gao, Shengfeng He, Alan Yuille, Yuyin Zhou, Cihang Xie
CVPR, 2022


Simulated Adversarial Testing of Face Recognition Models
Nataniel Ruiz, Adam Kortylewski, Weichao Qiu, Cihang Xie, Sarah Adel Bargal, Alan Yuille, Stan Sclaroff
CVPR, 2022


Fast AdvProp
Jieru Mei, Yucheng Han, Yutong Bai, Yixiao Zhang, Yingwei Li, Xianhang Li, Alan Yuille, Cihang Xie
ICLR, 2022


iBOT: Image BERT Pre-Training with Online Tokenizer
Jinghao Zhou, Chen Wei, Huiyu Wang, Wei Shen, Cihang Xie, Alan Yuille, Tao Kong
ICLR, 2022


2021

Are Transformers More Robust Than CNNs?
Yutong Bai, Jieru Mei, Alan Yuille, Cihang Xie
NeurIPS, 2021
The first benchmark that fairly compares Transformers with CNNs on robustness evaluations


Calibrating Concepts and Operations: Towards Symbolic Reasoning on Real Images
Zhuowan Li, Elias Stengel-Eskin, Yixiao Zhang, Cihang Xie, Quan Tran, Benjamin Van Durme, Alan Yuille
ICCV, 2021


Robust and Accurate Object Detection via Adversarial Learning
Xiangning Chen, Cihang Xie, Mingxing Tan, Li Zhang, Cho-Jui Hsieh, Boqing Gong
CVPR, 2021


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


2020

Towards Robust Representation Learning and Beyond
Cihang Xie
PhD Dissertation


Smooth Adversarial Training
Cihang Xie, Mingxing Tan, Boqing Gong, Alan Yuille, Quoc Le
Tech report, arXiv
State-of-the-art method for defending against adversarial attacks on ImageNet


PatchAttack: A Black-box Texture-based Attack with Reinforcement Learning
Chenglin Yang, Adam Kortylewski, Cihang Xie, Yinzhi Cao, Alan Yuille
ECCV, 2020


Regional Homogeneity: Towards Learning Transferable Universal Adversarial Perturbations Against Defenses
Yingwei Li, Song Bai, Cihang Xie, Zhenyu Liao, Xiaohui Shen, Alan Yuille
ECCV, 2020


Adversarial Examples Improve Image Recognition
Cihang Xie, Mingxing Tan, Boqing Gong, Jiang Wang, Alan Yuille, Quoc Le
CVPR, 2020
State-of-the-art ImageNet classifier without extra training data


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


Universal Physical Camouflage Attacks on Object Detectors
Lifeng Huang, Chengying Gao, Yuyin Zhou, Cihang Xie, Alan Yuille, Changqing Zou, Ning Liu
CVPR, 2020


Intriguing Properties of Adversarial Training at Scale
Cihang Xie, Alan Yuille
ICLR, 2020


Learning Transferable Adversarial Examples via Ghost Networks
Yingwei Li, Song Bai, Yuyin Zhou, Cihang Xie, Zhishuai Zhang, Alan Yuille
AAAI, 2020


2019

Feature Denoising for Improving Adversarial Robustness
Cihang Xie, Yuxin Wu, Laurens van der Maaten, Alan Yuille, Kaiming He
CVPR, 2019
The first ImageNet classifier that can successfully defend against strong white-box adversarial attacks


Improving Transferability of Adversarial Examples with Input Diversity
Cihang Xie, Zhishuai Zhang, Yuyin Zhou, Song Bai, Jianyu Wang, Zhou Ren, Alan Yuille
CVPR, 2019


2018

Mitigating Adversarial Effects Through Randomization
Cihang Xie, Jianyu Wang, Zhishuai Zhang, Zhou Ren, Alan Yuille
ICLR, 2018
The runner-up solution in the adversarial defense track of NIPS 2017 Adversarial Attacks and Defenses Competition


Single-Shot Object Detection with Enriched Semantics
Zhishuai Zhang, Siyuan Qiao, Cihang Xie, Wei Shen, Bo Wang, Alan Yuille
CVPR, 2018


DeepVoting: A Robust and Explainable Deep Network for Semantic Part Detection under Partial Occlusion
Zhishuai Zhang, Cihang Xie, Jianyu Wang, Lingxi Xie, Alan Yuille
CVPR, 2018


Visual Concepts and Compositional Voting
Jianyu Wang, Zhishuai Zhang, Cihang Xie, Yuyin Zhou, Vittal Premachandran, Jun Zhu, Lingxi Xie, Alan Yuille
Annals of Mathematical Sciences and Applications, 2018


2017

Adversarial Examples for Semantic Segmentation and Object Detection
Cihang Xie, Jianyu Wang, Zhishuai Zhang, Yuyin Zhou, Lingxi Xie, Alan Yuille
ICCV, 2017


Detecting Semantic Parts on Partially Occluded Objects
Jianyu Wang, Cihang Xie, Zhishuai Zhang, Jun Zhu, Lingxi Xie, Alan Yuille
BMVC, 2017



Open Sources

CleverHans Adversarial Examples Library

Adversarial Attacks on Face Recognition



Stolen from Jon Barron