Xiaohua Zhai
31 papers · 2019–2024 · 7 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+12 more ↓ Show less ↑
π Renaissance Researcher (6) π Interdisciplinary Bridge π Academic Marathon (5) π Conference Polyglot (7) πΊοΈ Taxonomy Completionist (50)
π
Conference Polyglot
(7)
π
Academic Marathon
(5)
πΊοΈ
Taxonomy Completionist
(50)
π₯
Mega-Team
(43)
π
Triple Crown
π€
Dynamic Duo
(22)
π
Trend Setter
π₯
Unstoppable
(6)
π
Century Club
(31)
ποΈ
Keyword Collector
(96)
β‘
Prolific Year
(8)
β
The Questioner
Conferences
NIPS (9)
CVPR (8)
ECCV (4)
ICML (4)
ICLR (3)
ICCV (2)
JMLR (1)
Top co-authors
Research topics
Keywords
image classification
(7)
vision transformer
(5)
contrastive learning
(5)
model scaling
(4)
self-supervised learning
(4)
transfer learning
(4)
vision-language model
(4)
convolutional neural network
(3)
image captioning
(3)
generative adversarial network
(3)
representation learning
(3)
domain generalization
(2)
unsupervised learning
(2)
zero-shot transfer
(2)
neural network
(2)
few-shot learning
(2)
computer vision
(2)
semi-supervised learning
(2)
distribution shift
(2)
policy optimization
(1)
Papers
LocCa: Visual Pretraining with Location-aware Captioners
NIPS 2024
On Scaling Up a Multilingual Vision and Language Model
CVPR 2024
CLIP the Bias: How Useful is Balancing Data in Multimodal Learning?
ICLR 2024
No Filter: Cultural and Socioeconomic Diversity in Contrastive Vision-Language Models
NIPS 2024
SILC: Improving Vision Language Pretraining with Self-Distillation
ECCV 2024
Scaling Vision Transformers to 22 Billion Parameters
ICML 2023
PaLI: A Jointly-Scaled Multilingual Language-Image Model
ICLR 2023
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design
NIPS 2023
Tuning Computer Vision Models With Task Rewards
ICML 2023
Three Towers: Flexible Contrastive Learning with Pretrained Image Models
NIPS 2023
FlexiViT: One Model for All Patch Sizes
CVPR 2023
Sigmoid Loss for Language Image Pre-Training
ICCV 2023
Image Captioners Are Scalable Vision Learners Too
NIPS 2023
Underspecification Presents Challenges for Credibility in Modern Machine Learning
JMLR 2022
Revisiting Neural Scaling Laws in Language and Vision
NIPS 2022
UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes
NIPS 2022
LiT: Zero-Shot Transfer With Locked-Image Text Tuning
CVPR 2022
Knowledge Distillation: A Good Teacher Is Patient and Consistent
CVPR 2022
Scaling Vision Transformers
CVPR 2022
A Simple Single-Scale Vision Transformer for Object Detection and Instance Segmentation
ECCV 2022
Simple Open-Vocabulary Object Detection with Vision Transformers
ECCV 2022
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
ICLR 2021
On Robustness and Transferability of Convolutional Neural Networks
CVPR 2021
MLP-Mixer: An all-MLP Architecture for Vision
NIPS 2021
Revisiting the Calibration of Modern Neural Networks
NIPS 2021
Big Transfer (BiT): General Visual Representation Learning
ECCV 2020
A Large-Scale Study on Regularization and Normalization in GANs
ICML 2019
Self-Supervised GANs via Auxiliary Rotation Loss
CVPR 2019
S4L: Self-Supervised Semi-Supervised Learning
ICCV 2019
High-Fidelity Image Generation With Fewer Labels
ICML 2019
Revisiting Self-Supervised Visual Representation Learning
CVPR 2019