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/zip-group/saq
공식 코드https://github.com/zip-group/spvit
공식 코드Pruning Self-attentions into Convolutional Layers in Single Path
https://github.com/ziplab/SN-Net
공식 코드https://github.com/ziplab/litv2
공식 코드https://github.com/ziplab/qtool
공식 코드https://github.com/ziplab/saq
공식 코드https://github.com/ziplab/spvit
공식 코드Pruning Self-attentions into Convolutional Layers in Single Path
https://github.com/ziquanliu/ICML2024-AT-UR
공식 코드The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks
https://github.com/ziquanliu/cvpr2023-twins
공식 코드https://github.com/ziweiwangthu/seernet
공식 코드Learning Accurate Performance Predictors for Ultrafast Automated Model Compression
https://github.com/ziyuwwang/dynamixer
공식 코드https://github.com/zj10/NCMN
공식 코드Removing the Feature Correlation Effect of Multiplicative Noise
https://github.com/zjlab-ammi/demix
공식 코드https://github.com/zjlab-ammi/vae4ood
공식 코드Unsupervised Out-of-Distribution Detection by Restoring Lossy Inputs with Variational Autoencoder
https://github.com/zjukg/DUET
공식 코드DUET: Cross-modal Semantic Grounding for Contrastive Zero-shot Learning
https://github.com/zjukg/dozsl
공식 코드https://github.com/zjukg/kg-mm-survey
공식 코드Knowledge Graphs Meet Multi-Modal Learning: A Comprehensive Survey
https://github.com/zjukg/kgtransformer
공식 코드Structure Pretraining and Prompt Tuning for Knowledge Graph Transfer
https://github.com/zjyaccount/mtmsd
공식 코드Exploring Multi-Timestep Multi-Stage Diffusion Features for Hyperspectral Image Classification
https://github.com/zjysteven/DVERGE
공식 코드DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of Ensembles
https://github.com/zjysteven/mixoe
공식 코드Mixture Outlier Exposure: Towards Out-of-Distribution Detection in Fine-grained Environments
https://github.com/zk-zhou/spikformer
공식 코드https://github.com/zki-ph-imageanalysis/next-generation-loss
공식 코드https://github.com/zkkli/psaq-vit
공식 코드PSAQ-ViT V2: Towards Accurate and General Data-Free Quantization for Vision Transformers
https://github.com/zkzhang98/microseg
공식 코드Mining Unseen Classes via Regional Objectness: A Simple Baseline for Incremental Segmentation
https://github.com/zlkong/awesome-token-compression-reduction
공식 코드https://github.com/zmtomorrow/nelloc
공식 코드On the Out-of-distribution Generalization of Probabilistic Image Modelling
https://github.com/zohaib-khan5040/key-driven-gqa
공식 코드Beyond Uniform Query Distribution: Key-Driven Grouped Query Attention
https://github.com/zs1314/microscopic-mamba
공식 코드Microscopic-Mamba: Revealing the Secrets of Microscopic Images with Just 4M Parameters
https://github.com/zs670980918/msa-conv
공식 코드https://github.com/zstarn70/rlrr
공식 코드Low-Rank Rescaled Vision Transformer Fine-Tuning: A Residual Design Approach
https://github.com/ztx-100/efficient_vit_with_dw
공식 코드Depth-Wise Convolutions in Vision Transformers for Efficient Training on Small Datasets
https://github.com/zuiran/splicemix
공식 코드https://github.com/zuwenqiang/ept
공식 코드Embedded Prompt Tuning: Towards Enhanced Calibration of Pretrained Models for Medical Images
https://github.com/zwx8981/DBCNN-PyTorch
공식 코드Blind Image Quality Assessment Using A Deep Bilinear Convolutional Neural Network
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.