https://github.com/gihyunkim/Exploring-Adversarial-Robustness-of-ViT-in-the-Spectral-Perspective
공식 코드Exploring Adversarial Robustness of Vision Transformers in the Spectral Perspective
Papers with Code 아카이브
Image Classification
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Image Classification is a fundamental task in vision recognition that aims to understand and categorize an image as a whole under a specific label. Unlike object detection, which involves classification and location of multiple objects within an image, image classification typically pertains to single-object images. When the classification becomes highly detailed or reaches instance-level, it is often referred to as image retrieval, which also involves finding similar images in a large database.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/gimme1dollar/gradcam-consistency-semi-sup
공식 코드Semi-supervised Image Classification with Grad-CAM Consistency
https://github.com/gingl/cmpa
공식 코드https://github.com/gioannides/gaussian-adaptive-attention
공식 코드https://github.com/giobin/applied_intelligence_sparsity
공식 코드Regularization-based Pruning of Irrelevant Weights in Deep Neural Architectures
https://github.com/giorgiop/loss-correction
공식 코드Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach
https://github.com/giovannicina/selecting_ood_detector
공식 코드Out-of-Distribution Detection for Medical Applications: Guidelines for Practical Evaluation
https://github.com/gist-ailab/block-selection-for-ood-detection
공식 코드Block Selection Method for Using Feature Norm in Out-of-distribution Detection
https://github.com/gistairc/MUSIC4P3
공식 코드https://github.com/git-disl/LRBench
공식 코드Demystifying Learning Rate Policies for High Accuracy Training of Deep Neural Networks
https://github.com/github-songsong/fine-grained-pointcloud-object-dataset
공식 코드Enhancing Fine-Grained 3D Object Recognition using Hybrid Multi-Modal Vision Transformer-CNN Models
https://github.com/gizi1/NormKD
공식 코드https://github.com/glassroom/heinsen_routing
공식 코드https://github.com/glemhel/activationsgradientscompressionformp
공식 코드Activations and Gradients Compression for Model-Parallel Training
https://github.com/glhr/beyond-auroc
공식 코드Beyond AUROC & co. for evaluating out-of-distribution detection performance
https://github.com/glhr/ood-labelnoise
공식 코드A noisy elephant in the room: Is your out-of-distribution detector robust to label noise?
https://github.com/gm3g11/nns-emd
공식 코드Efficient approximation of Earth Mover's Distance Based on Nearest Neighbor Search
https://github.com/gmberton/cosplace
공식 코드Rethinking Visual Geo-localization for Large-Scale Applications
https://github.com/gmr523/pop
공식 코드Out-of-Distribution Detection with Prototypical Outlier Proxy
https://github.com/gmum/few-shot-hypernets-public
공식 코드https://github.com/gmum/geo-gcn
공식 코드https://github.com/gmum/protopool
공식 코드Interpretable Image Classification with Differentiable Prototypes Assignment
https://github.com/gohypergiant/research-autodc
공식 코드https://github.com/gokberkgul/self-learning-transformer-mil
공식 코드Histopathological Image Classification based on Self-Supervised Vision Transformer and Weak Labels
https://github.com/gokriznastic/HybridSN
공식 코드HybridSN: Exploring 3D-2D CNN Feature Hierarchy for Hyperspectral Image Classification
https://github.com/gokulkarthik/deformable-detr
공식 코드An Empirical Study Of Self-supervised Learning Approaches For Object Detection With Transformers
https://github.com/gokulkarthik/detr
공식 코드An Empirical Study Of Self-supervised Learning Approaches For Object Detection With Transformers
https://github.com/gokyeongryeol/tbu
공식 코드https://github.com/goldblum/AdversarialQuerying
공식 코드Adversarially Robust Few-Shot Learning: A Meta-Learning Approach
https://github.com/gomes-lab/AiSciVision
공식 코드AiSciVision: A Framework for Specializing Large Multimodal Models in Scientific Image Classification
https://github.com/gomezzz/MSMatch
공식 코드MSMatch: Semi-Supervised Multispectral Scene Classification with Few Labels
https://github.com/google-deepmind/relicv2
공식 코드https://github.com/google-deepmind/visual-memory
공식 코드https://github.com/google-research/OOD-failures
공식 코드Understanding the Failure Modes of Out-of-Distribution Generalization
https://github.com/google-research/adapter-bert
공식 코드https://github.com/google-research/augmix
공식 코드AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.