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2106.04803
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CoAtNet: Marrying Convolution and Attention for All Data Sizes
Neural Information Processing Systems (NeurIPS), 2021
9 June 2021
Zihang Dai
Hanxiao Liu
Quoc V. Le
Mingxing Tan
ViT
Re-assign community
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Papers citing
"CoAtNet: Marrying Convolution and Attention for All Data Sizes"
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FastViT: A Fast Hybrid Vision Transformer using Structural Reparameterization
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J. Gabriel
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Enhancing Multiple Reliability Measures via Nuisance-extended Information Bottleneck
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Exploiting Unlabelled Photos for Stronger Fine-Grained SBIR
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A. Bhunia
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Pinaki Nath Chowdhury
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24 Mar 2023
CAT-Seg: Cost Aggregation for Open-Vocabulary Semantic Segmentation
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Seokju Cho
Heeseong Shin
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Anurag Arnab
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Seung Wook Kim
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355
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21 Mar 2023
Large AI Models in Health Informatics: Applications, Challenges, and the Future
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Wu Yuan
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Convolutions, Transformers, and their Ensembles for the Segmentation of Organs at Risk in Radiation Treatment of Cervical Cancer
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101
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Cross-Modal Causal Intervention for Medical Report Generation
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Weixing Chen
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328
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CrossFormer++: A Versatile Vision Transformer Hinging on Cross-scale Attention
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FFT-based Dynamic Token Mixer for Vision
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Pyramid Pixel Context Adaption Network for Medical Image Classification with Supervised Contrastive Learning
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Zunjie Xiao
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Yan Hu
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275
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Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models
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Francesco Croce
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Self-attention in Vision Transformers Performs Perceptual Grouping, Not Attention
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Image as Set of Points
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Guozhen Zhang
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Teaching CLIP to Count to Ten
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Ariel Ephrat
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Device Tuning for Multi-Task Large Model
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Xuanchen Hou
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PolyFormer: Referring Image Segmentation as Sequential Polygon Generation
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Hui Ding
Zhaowei Cai
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Symbolic Discovery of Optimization Algorithms
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Xiangning Chen
Chen Liang
Da Huang
Esteban Real
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Xuanyi Dong
Thang Luong
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Quoc V. Le
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Progressive Meta-Pooling Learning for Lightweight Image Classification Model
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A Structural Approach to the Design of Domain Specific Neural Network Architectures
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Efficient Activation Function Optimization through Surrogate Modeling
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374
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ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders
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Saining Xie
SyDa
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1,289
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Exploring Vision Transformers as Diffusion Learners
He Cao
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Xianbiao Qi
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Representation Separation for Semantic Segmentation with Vision Transformers
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Huihui Pan
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Huijun Gao
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179
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MixupE: Understanding and Improving Mixup from Directional Derivative Perspective
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Vikas Verma
Sarthak Mittal
Wai Hoh Tang
Hieu H. Pham
Arno Solin
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What Makes for Good Tokenizers in Vision Transformer?
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Yi Zhu
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Jiaya Jia
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219
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Universal Object Detection with Large Vision Model
International Journal of Computer Vision (IJCV), 2022
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Ju Hu
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368
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Saeed Khorram
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OAMixer: Object-aware Mixing Layer for Vision Transformers
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260
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Open Vocabulary Semantic Segmentation with Patch Aligned Contrastive Learning
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Jishnu Mukhoti
Tsung-Yu Lin
Omid Poursaeed
Rui Wang
Ashish Shah
Juil Sock
Ser-Nam Lim
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263
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09 Dec 2022
Deep Incubation: Training Large Models by Divide-and-Conquering
IEEE International Conference on Computer Vision (ICCV), 2022
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Yulin Wang
Jiangwei Yu
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Yu Cao
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239
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MixBoost: Improving the Robustness of Deep Neural Networks by Boosting Data Augmentation
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Lightweight Structure-Aware Attention for Visual Understanding
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F. M. Castro
M. Marín-Jiménez
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29 Nov 2022
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Geonho Hwang
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Fast-iTPN: Integrally Pre-Trained Transformer Pyramid Network with Token Migration
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Yunjie Tian
Lingxi Xie
Jihao Qiu
Jianbin Jiao
Yaowei Wang
Qi Tian
Qixiang Ye
ViT
196
19
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23 Nov 2022
Conv2Former: A Simple Transformer-Style ConvNet for Visual Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Qibin Hou
Cheng Lu
Mingg-Ming Cheng
Jiashi Feng
ViT
230
214
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Vision Transformer with Super Token Sampling
Huaibo Huang
Xiaoqiang Zhou
Jie Cao
Xiao-Yu Zhang
Tieniu Tan
ViT
281
96
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21 Nov 2022
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