Poster "image classification" Papers
133 papers found • Page 1 of 3
Conference
Accessing Vision Foundation Models via ImageNet-1K
Yitian Zhang, Xu Ma, Yue Bai et al.
AdaFisher: Adaptive Second Order Optimization via Fisher Information
Damien GOMES, Yanlei Zhang, Eugene Belilovsky et al.
AdaMSS: Adaptive Multi-Subspace Approach for Parameter-Efficient Fine-Tuning
Jingjing Zheng, Wanglong Lu, Yiming Dong et al.
Advancing Out-of-Distribution Detection via Local Neuroplasticity
Alessandro Canevaro, Julian Schmidt, Sajad Marvi et al.
Adversarial Robustness of Discriminative Self-Supervised Learning in Vision
Ömer Veysel Çağatan, Ömer TAL, M. Emre Gursoy
A Hidden Stumbling Block in Generalized Category Discovery: Distracted Attention
Qiyu Xu, Zhanxuan Hu, Yu Duan et al.
Alias-Free ViT: Fractional Shift Invariance via Linear Attention
Hagay Michaeli, Daniel Soudry
As large as it gets – Studying Infinitely Large Convolutions via Neural Implicit Frequency Filters
Margret Keuper, Julia Grabinski, Janis Keuper
Automatic Visual Instrumental Variable Learning for Confounding-Resistant Domain Generalization
Fuyuan CAO, Shichang Qiao, Kui Yu et al.
Bayesian Test-Time Adaptation for Vision-Language Models
Lihua Zhou, Mao Ye, Shuaifeng Li et al.
Beyond Random: Automatic Inner-loop Optimization in Dataset Distillation
Muquan Li, Hang Gou, Dongyang Zhang et al.
Can Generative Geospatial Diffusion Models Excel as Discriminative Geospatial Foundation Models?
Yuru Jia, Valerio Marsocci, Ziyang Gong et al.
Certifying Deep Network Risks and Individual Predictions with PAC-Bayes Loss via Localized Priors
Wen Dong
CHiQPM: Calibrated Hierarchical Interpretable Image Classification
Thomas Norrenbrock, Timo Kaiser, Sovan Biswas et al.
Collapse-Proof Non-Contrastive Self-Supervised Learning
EMANUELE SANSONE, Tim Lebailly, Tinne Tuytelaars
Convolution Goes Higher-Order: A Biologically Inspired Mechanism Empowers Image Classification
Simone Azeglio, Olivier Marre, Peter Neri et al.
Correlated Low-Rank Adaptation for ConvNets
Wu Ran, Weijia Zhang, ShuYang Pang et al.
DCT-CryptoNets: Scaling Private Inference in the Frequency Domain
Arjun Roy, Kaushik Roy
Deep Taxonomic Networks for Unsupervised Hierarchical Prototype Discovery
Zekun Wang, Ethan Haarer, Tianyi Zhu et al.
Directional Gradient Projection for Robust Fine-Tuning of Foundation Models
Chengyue Huang, Junjiao Tian, Brisa Maneechotesuwan et al.
Directional Label Diffusion Model for Learning from Noisy Labels
Senyu Hou, Gaoxia Jiang, Jia Zhang et al.
Discovering Influential Neuron Path in Vision Transformers
Yifan Wang, Yifei Liu, Yingdong Shi et al.
DKDR: Dynamic Knowledge Distillation for Reliability in Federated Learning
Yueyang Yuan, Wenke Huang, Guancheng Wan et al.
DuSA: Fast and Accurate Dual-Stage Sparse Attention Mechanism Accelerating Both Training and Inference
Chong Wu, Jiawang Cao, Renjie Xu et al.
DVHGNN: Multi-Scale Dilated Vision HGNN for Efficient Vision Recognition
Caoshuo Li, Tanzhe Li, Xiaobin Hu et al.
EA-KD: Entropy-based Adaptive Knowledge Distillation
Chi-Ping Su, Ching-Hsun Tseng, Bin Pu et al.
EfficientViM: Efficient Vision Mamba with Hidden State Mixer based State Space Duality
Sanghyeok Lee, Joonmyung Choi, Hyunwoo J. Kim
End-to-End Implicit Neural Representations for Classification
Alexander Gielisse, Jan van Gemert
Enhancing Transformers Through Conditioned Embedded Tokens
Hemanth Saratchandran, Simon Lucey
Enhancing Visual Prompting through Expanded Transformation Space and Overfitting Mitigation
Shohei Enomoto
EvA: Erasing Spurious Correlations with Activations
Qiyuan He, Kai Xu, Angela Yao
GSBA$^K$: $top$-$K$ Geometric Score-based Black-box Attack
Md Farhamdur Reza, Richeng Jin, Tianfu Wu et al.
GSPN-2: Efficient Parallel Sequence Modeling
Hongjun Wang, yitong jiang, Collin McCarthy et al.
H-SPLID: HSIC-based Saliency Preserving Latent Information Decomposition
Lukas Miklautz, Chengzhi Shi, Andrii Shkabrii et al.
Hypergraph Vision Transformers: Images are More than Nodes, More than Edges
Joshua Fixelle
I Am Big, You Are Little; I Am Right, You Are Wrong
David A Kelly, Akchunya Chanchal, Nathan Blake
Is Large-scale Pretraining the Secret to Good Domain Generalization?
Piotr Teterwak, Kuniaki Saito, Theodoros Tsiligkaridis et al.
Learning Mask Invariant Mutual Information for Masked Image Modeling
Tao Huang, Yanxiang Ma, Shan You et al.
Local Dense Logit Relations for Enhanced Knowledge Distillation
Liuchi Xu, Kang Liu, Jinshuai Liu et al.
LoKi: Low-dimensional KAN for Efficient Fine-tuning Image Models
Xuan Cai, Renjie Pan, Hua Yang
MambaOut: Do We Really Need Mamba for Vision?
Weihao Yu, Xinchao Wang
Metric-Driven Attributions for Vision Transformers
Chase Walker, Sumit Jha, Rickard Ewetz
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.
Provably Reliable Conformal Prediction Sets in the Presence of Data Poisoning
Yan Scholten, Stephan Günnemann