"image classification" Papers
159 papers found • Page 2 of 4
Conference
MobileODE: An Extra Lightweight Network
Le Yu, Jun Wu, Bo Gou et al.
Multi-Kernel Correlation-Attention Vision Transformer for Enhanced Contextual Understanding and Multi-Scale Integration
Hongkang Zhang, Shao-Lun Huang, Ercan KURUOGLU et al.
MUNBa: Machine Unlearning via Nash Bargaining
Jing Wu, Mehrtash Harandi
Neural Tangent Knowledge Distillation for Optical Convolutional Networks
Jinlin Xiang, Minho Choi, Yubo Zhang et al.
On Large Multimodal Models as Open-World Image Classifiers
Alessandro Conti, Massimiliano Mancini, Enrico Fini et al.
Optimal Control for Transformer Architectures: Enhancing Generalization, Robustness and Efficiency
Kelvin Kan, Xingjian Li, Benjamin Zhang et al.
Parameter Efficient Fine-tuning via Explained Variance Adaptation
Fabian Paischer, Lukas Hauzenberger, Thomas Schmied et al.
Polyline Path Masked Attention for Vision Transformer
Zhongchen Zhao, Chaodong Xiao, Hui LIN et al.
Provably Reliable Conformal Prediction Sets in the Presence of Data Poisoning
Yan Scholten, Stephan Günnemann
RainbowPrompt: Diversity-Enhanced Prompt-Evolving for Continual Learning
Kiseong Hong, Gyeong-Hyeon Kim, Eunwoo Kim
Rectifying Magnitude Neglect in Linear Attention
Qihang Fan, Huaibo Huang, Yuang Ai et al.
REP: Resource-Efficient Prompting for Rehearsal-Free Continual Learning
Sungho Jeon, Xinyue Ma, Kwang In Kim et al.
Semantic Equitable Clustering: A Simple and Effective Strategy for Clustering Vision Tokens
Qihang Fan, Huaibo Huang, Mingrui Chen et al.
Sharpness-Aware Minimization: General Analysis and Improved Rates
Dimitris Oikonomou, Nicolas Loizou
Sparse autoencoders reveal selective remapping of visual concepts during adaptation
Hyesu Lim, Jinho Choi, Jaegul Choo et al.
Spectral State Space Model for Rotation-Invariant Visual Representation Learning
Sahar Dastani, Ali Bahri, Moslem Yazdanpanah et al.
SpikePack: Enhanced Information Flow in Spiking Neural Networks with High Hardware Compatibility
Guobin Shen, Jindong Li, Tenglong Li et al.
Spiking Neural Networks Need High-Frequency Information
Yuetong Fang, Deming Zhou, Ziqing Wang et al.
SpiLiFormer: Enhancing Spiking Transformers with Lateral Inhibition
Zeqi Zheng, Yanchen Huang, Yingchao Yu et al.
Synergy and Diversity in CLIP: Enhancing Performance Through Adaptive Backbone Ensembling
Cristian Rodriguez-Opazo, Ehsan Abbasnejad, Damien Teney et al.
Synthetic-powered predictive inference
Meshi Bashari, Roy Maor Lotan, Yonghoon Lee et al.
Task Vector Quantization for Memory-Efficient Model Merging
Youngeun Kim, Seunghwan Lee, Aecheon Jung et al.
The AdEMAMix Optimizer: Better, Faster, Older
Matteo Pagliardini, Pierre Ablin, David Grangier
Till the Layers Collapse: Compressing a Deep Neural Network Through the Lenses of Batch Normalization Layers.
Zhu Liao, Nour Hezbri, Victor Quétu et al.
TinyViM: Frequency Decoupling for Tiny Hybrid Vision Mamba
Xiaowen Ma, Zhen-Liang Ni, Xinghao Chen
Understanding and Improving Adversarial Robustness of Neural Probabilistic Circuits
Weixin Chen, Han Zhao
ViG: Linear-complexity Visual Sequence Learning with Gated Linear Attention
Bencheng Liao, Xinggang Wang, Lianghui Zhu et al.
Visual-RFT: Visual Reinforcement Fine-Tuning
Ziyu Liu, Zeyi Sun, Yuhang Zang et al.
VSSD: Vision Mamba with Non-Causal State Space Duality
Yuheng Shi, Mingjia Li, Minjing Dong et al.
When majority rules, minority loses: bias amplification of gradient descent
François Bachoc, Jerome Bolte, Ryan Boustany et al.
Active Generation for Image Classification
Tao Huang, Jiaqi Liu, Shan You et al.
Adversarial Robustness Limits via Scaling-Law and Human-Alignment Studies
Brian Bartoldson, James Diffenderfer, Konstantinos Parasyris et al.
Agglomerative Token Clustering
Joakim Bruslund Haurum, Sergio Escalera, Graham W. Taylor et al.
AMD: Automatic Multi-step Distillation of Large-scale Vision Models
Cheng Han, Qifan Wang, Sohail A Dianat et al.
Amortized Variational Deep Kernel Learning
Alan Matias, César Lincoln Mattos, Joao Paulo Gomes et al.
AMPA: Adaptive Mixed Precision Allocation for Low-Bit Integer Training
Li Ding, Wen Fei, Yuyang Huang et al.
Anytime Continual Learning for Open Vocabulary Classification
Zhen Zhu, Yiming Gong, Derek Hoiem
Asynchronous Bioplausible Neuron for Spiking Neural Networks for Event-Based Vision
Hussain Sajwani, Dimitrios Makris, Yahya Zweiri et al.
AttnZero: Efficient Attention Discovery for Vision Transformers
Lujun Li, Zimian Wei, Peijie Dong et al.
Boosting Adversarial Transferability across Model Genus by Deformation-Constrained Warping
Qinliang Lin, Cheng Luo, Zenghao Niu et al.
Catch-Up Mix: Catch-Up Class for Struggling Filters in CNN
Minsoo Kang, Minkoo Kang, Suhyun Kim
Cocktail Universal Adversarial Attack on Deep Neural Networks
Shaoxin Li, Xiaofeng Liao, Xin Che et al.
Data Adaptive Traceback for Vision-Language Foundation Models in Image Classification
Long-Fei Li, Peng Zhao, Zhi-Hua Zhou
DataDream: Few-shot Guided Dataset Generation
Jae Myung Kim, Jessica Bader, Stephan Alaniz et al.
Decoupling Feature Extraction and Classification Layers for Calibrated Neural Networks
Mikkel Jordahn, Pablo Olmos
Deep Nets with Subsampling Layers Unwittingly Discard Useful Activations at Test-Time
Chiao-An Yang, Ziwei Liu, Raymond Yeh
DenseNets Reloaded: Paradigm Shift Beyond ResNets and ViTs
Donghyun Kim, Byeongho Heo, Dongyoon Han
Differentiable Model Scaling using Differentiable Topk
Kai Liu, Ruohui Wang, Jianfei Gao et al.
Do text-free diffusion models learn discriminative visual representations?
Soumik Mukhopadhyay, Matthew Gwilliam, Yosuke Yamaguchi et al.
DP-AdamBC: Your DP-Adam Is Actually DP-SGD (Unless You Apply Bias Correction)
Qiaoyue Tang, Frederick Shpilevskiy, Mathias Lécuyer