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/cheliu-computation/m-flag-miccai2023
공식 코드https://github.com/cheliu-computation/medsyn-replearn
공식 코드https://github.com/chenchenzong/dpc
공식 코드Dirichlet-Based Prediction Calibration for Learning with Noisy Labels
https://github.com/chendelong1999/remoteclip
공식 코드RemoteCLIP: A Vision Language Foundation Model for Remote Sensing
https://github.com/chenfan95/sign-maml
공식 코드Sign-MAML: Efficient Model-Agnostic Meta-Learning by SignSGD
https://github.com/chengcv/J3S
공식 코드Reconciliation of Statistical and Spatial Sparsity For Robust Image and Image-Set Classification
https://github.com/chengcv/dfrfs
공식 코드Disentangled Feature Representation for Few-shot Image Classification
https://github.com/chenghan111/dnc
공식 코드https://github.com/chengjin-git/hmil
공식 코드HMIL: Hierarchical Multi-Instance Learning for Fine-Grained Whole Slide Image Classification
https://github.com/chengkang520/gate-with-inhibition
공식 코드https://github.com/chengqingli/ficnet
공식 코드https://github.com/chengtan9907/OpenSTL
공식 코드https://github.com/chengtan9907/co-training-based_noisy-label-learning
공식 코드Co-learning: Learning from Noisy Labels with Self-supervision
https://github.com/chenhaoxing/MACL_ICML2023
공식 코드Model-Aware Contrastive Learning: Towards Escaping the Dilemmas
https://github.com/chenhaoxing/ssformers
공식 코드https://github.com/chenhongyiyang/gpvit
공식 코드GPViT: A High Resolution Non-Hierarchical Vision Transformer with Group Propagation
https://github.com/chenhongyiyang/plainmamba
공식 코드PlainMamba: Improving Non-Hierarchical Mamba in Visual Recognition
https://github.com/chenhongyiyang/ppal
공식 코드https://github.com/chenhsing/ssp3d
공식 코드Semi-Supervised Single-View 3D Reconstruction via Prototype Shape Priors
https://github.com/chenhsing/svformer
공식 코드SVFormer: Semi-supervised Video Transformer for Action Recognition
https://github.com/chenmc1996/Multi-Head-Co-Training
공식 코드https://github.com/chenmingxiang110/AugNet
공식 코드AugNet: End-to-End Unsupervised Visual Representation Learning with Image Augmentation
https://github.com/chenning0115/spectraldiff
공식 코드SpectralDiff: A Generative Framework for Hyperspectral Image Classification with Diffusion Models
https://github.com/chenpf1025/IDN
공식 코드Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise
https://github.com/chenpf1025/RobustnessAccuracy
공식 코드Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels
https://github.com/chenpf1025/noisy_label_understanding_utilizing
공식 코드Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels
https://github.com/chensy7/efficient-vit
공식 코드Compressing Vision Transformers for Low-Resource Visual Learning
https://github.com/chenxi116/PNASNet.TF
공식 코드https://github.com/chenxi116/PNASNet.pytorch
공식 코드https://github.com/chenxiangma/auglocal
공식 코드Scaling Supervised Local Learning with Augmented Auxiliary Networks
https://github.com/chenyangli-97/nn-bcd
공식 코드On Model Compression for Neural Networks: Framework, Algorithm, and Convergence Guarantee
https://github.com/chenzhe207/FDLSR
공식 코드Fisher Discriminative Least Squares Regression for Image Classification
https://github.com/chhwang/cmcl
공식 코드https://github.com/chihhuiho/disco
공식 코드https://github.com/chintantrivedi/lpsoftmaxloss
공식 코드Revisiting lp-constrained Softmax Loss: A Comprehensive Study
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.