https://github.com/VIPriors/vipriors-challenges-toolkit
공식 코드VIPriors 1: Visual Inductive Priors for Data-Efficient Deep Learning Challenges
Papers with Code 아카이브
Image Classification
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- 평가표
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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/VISION-SJTU/IoUattack
공식 코드IoU Attack: Towards Temporally Coherent Black-Box Adversarial Attack for Visual Object Tracking
https://github.com/VITA-Group/BNN_NoBN
공식 코드"BNN - BN = ?": Training Binary Neural Networks without Batch Normalization
https://github.com/VITA-Group/SViTE
공식 코드Chasing Sparsity in Vision Transformers: An End-to-End Exploration
https://github.com/VLL-HD/trustworthy_GCs
공식 코드Generative Classifiers as a Basis for Trustworthy Image Classification
https://github.com/VTCSML/Constrained-Labeling-for-Weakly-Supervised-Learning
공식 코드https://github.com/Valentyn1997/oct-diagn-semi-supervised
공식 코드Matching the Clinical Reality: Accurate OCT-Based Diagnosis From Few Labels
https://github.com/Vanint/TADE-AgnosticLT
공식 코드Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition
https://github.com/VectorInstitute/gram-ood-detection
공식 코드Detecting Out-of-Distribution Examples with In-distribution Examples and Gram Matrices
https://github.com/VedikaSrivastava/GeoMapper
공식 코드https://github.com/VeriDeep/DLV
공식 코드https://github.com/VeriXAI/Outside-the-Box
공식 코드Outside the Box: Abstraction-Based Monitoring of Neural Networks
https://github.com/ViTAE-Transformer/ViTAE-Transformer
공식 코드ViTAEv2: Vision Transformer Advanced by Exploring Inductive Bias for Image Recognition and Beyond
https://github.com/VicenteVivan/geo-clip
공식 코드https://github.com/Vincent-HKUSTGZ/FragFake
공식 코드FragFake: A Dataset for Fine-Grained Detection of Edited Images with Vision Language Models
https://github.com/VisaoComputacional/mira
공식 코드MIRA: A Computational Neuro-Based Cognitive Architecture Applied to Movie Recommender Systems
https://github.com/Vision-CAIR/LongVU
공식 코드LongVU: Spatiotemporal Adaptive Compression for Long Video-Language Understanding
https://github.com/VisionLearningGroup/DAL
공식 코드https://github.com/VisionLearningGroup/SANE
공식 코드Why do These Match? Explaining the Behavior of Image Similarity Models
https://github.com/VisionLearningGroup/taskcv-2017-public
공식 코드https://github.com/Visual-Attention-Network/VAN-Classification
공식 코드https://github.com/Waasem/RobDanns
공식 코드Exploring Robust Architectures for Deep Artificial Neural Networks
https://github.com/WangJingyao07/MetaLearning-Lab
공식 코드AwesomeMeta+: A Mixed-Prototyping Meta-Learning System Supporting AI Application Design Anywhere
https://github.com/WangLibo1995/GeoSeg
공식 코드https://github.com/WangWenhao0716/Attentive-WaveBlock
공식 코드https://github.com/WangYueFt/rfs
공식 코드Rethinking Few-Shot Image Classification: a Good Embedding Is All You Need?
https://github.com/WeiQijie/retinal-lesions
공식 코드https://github.com/WeiWangTrento/Robust-Differentiable-SVD
공식 코드https://github.com/WeixiongLin/PMC-CLIP
공식 코드PMC-CLIP: Contrastive Language-Image Pre-training using Biomedical Documents
https://github.com/Wenxuan-1119/TransBTS
공식 코드TransBTS: Multimodal Brain Tumor Segmentation Using Transformer
https://github.com/Westlake-AI/A2MIM
공식 코드Architecture-Agnostic Masked Image Modeling -- From ViT back to CNN
https://github.com/Westlake-AI/Awesome-Mixup
공식 코드https://github.com/Westlake-AI/MogaNet
공식 코드https://github.com/Westlake-AI/SemiReward
공식 코드SemiReward: A General Reward Model for Semi-supervised Learning
https://github.com/Westlake-AI/openmixup
공식 코드AutoMix: Unveiling the Power of Mixup for Stronger Classifiers
https://github.com/WilliamYi96/HGR-Net
공식 코드Exploring Hierarchical Graph Representation for Large-Scale Zero-Shot Image Classification
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.