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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/decurtoydiaz/learning_with_signatures
공식 코드https://github.com/deep-optimization/scalekd
공식 코드ScaleKD: Strong Vision Transformers Could Be Excellent Teachers
https://github.com/deep-spin/unn
공식 코드https://github.com/deep-unlearn/Big_Data_From_Space_2017
공식 코드https://github.com/deepglint/unicom
공식 코드Unicom: Universal and Compact Representation Learning for Image Retrieval
https://github.com/deeplearning-wisc/MOOD
공식 코드https://github.com/deeplearning-wisc/cider
공식 코드How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection?
https://github.com/deeplearning-wisc/dice
공식 코드DICE: Leveraging Sparsification for Out-of-Distribution Detection
https://github.com/deeplearning-wisc/dream-ood
공식 코드Dream the Impossible: Outlier Imagination with Diffusion Models
https://github.com/deeplearning-wisc/id_label
공식 코드When and How Does In-Distribution Label Help Out-of-Distribution Detection?
https://github.com/deeplearning-wisc/large_scale_ood
공식 코드MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space
https://github.com/deeplearning-wisc/multi-label-ood
공식 코드Can multi-label classification networks know what they don't know?
https://github.com/deeplearning-wisc/pg-dro
공식 코드Distributionally Robust Optimization with Probabilistic Group
https://github.com/deeplearning-wisc/poem
공식 코드https://github.com/deeplearning-wisc/sorl
공식 코드A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning
https://github.com/deeplearning-wisc/spurious_ood
공식 코드On the Impact of Spurious Correlation for Out-of-distribution Detection
https://github.com/deeplearning-wisc/stud
공식 코드Unknown-Aware Object Detection: Learning What You Don't Know from Videos in the Wild
https://github.com/deeplearning-wisc/vos
공식 코드VOS: Learning What You Don't Know by Virtual Outlier Synthesis
https://github.com/deeplearningmethods/averaged-adam
공식 코드https://github.com/deepmind/deepmind-research
공식 코드Unsupervised Learning of Object Keypoints for Perception and Control
https://github.com/deepmind/deepmind-research/tree/master/byol
공식 코드Bootstrap your own latent: A new approach to self-supervised Learning
https://github.com/deepmind/deepmind-research/tree/master/nfnets
공식 코드High-Performance Large-Scale Image Recognition Without Normalization
https://github.com/deepmind/deepmind-research/tree/master/perceiver
공식 코드https://github.com/deepmind/jax_privacy
공식 코드Unlocking High-Accuracy Differentially Private Image Classification through Scale
https://github.com/deepmind/jax_verify
공식 코드Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications
https://github.com/deeprobust/DeepRobust
공식 코드Understanding Local Robustness of Deep Neural Networks under Natural Variations
https://github.com/deepskies/gcnn_da
공식 코드SIDDA: SInkhorn Dynamic Domain Adaptation for Image Classification with Equivariant Neural Networks
https://github.com/deepskies/sidda
공식 코드SIDDA: SInkhorn Dynamic Domain Adaptation for Image Classification with Equivariant Neural Networks
https://github.com/dehshibi/advise
공식 코드ADVISE: ADaptive Feature Relevance and VISual Explanations for Convolutional Neural Networks
https://github.com/deib-polimi/dillema
공식 코드DILLEMA: Diffusion and Large Language Models for Multi-Modal Augmentation
https://github.com/delay-xili/sdnet
공식 코드Revisiting Sparse Convolutional Model for Visual Recognition
https://github.com/demidovd98/fgic_lowd
공식 코드Extract More from Less: Efficient Fine-Grained Visual Recognition in Low-Data Regimes
https://github.com/demidovd98/sm-vit
공식 코드Salient Mask-Guided Vision Transformer for Fine-Grained Classification
https://github.com/demolakstate/eGAN_addressing_class_imbalance_with_transfer_learning_on_GAN
공식 코드eGAN: Unsupervised approach to class imbalance using transfer learning
https://github.com/dengweihuan/SSDGL
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.