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/ceezh/silvr
공식 코드https://github.com/cemos-is/genformer
공식 코드https://github.com/cemos-is/robust-minisets
공식 코드https://github.com/cerebras/online-normalization
공식 코드https://github.com/cerebrasresearch/revbifpn
공식 코드RevBiFPN: The Fully Reversible Bidirectional Feature Pyramid Network
https://github.com/cewu/ptnl
공식 코드Why Is Prompt Tuning for Vision-Language Models Robust to Noisy Labels?
https://github.com/cfchen-duke/ProtoPNet
공식 코드This Looks Like That: Deep Learning for Interpretable Image Recognition
https://github.com/cfifty/CAML
공식 코드https://github.com/cfsantos/MaxDropout-torch
공식 코드MaxDropout: Deep Neural Network Regularization Based on Maximum Output Values
https://github.com/cfzd/FcaNet
공식 코드https://github.com/cgaroufis/mscol_smc23
공식 코드https://github.com/cgaroufis/msspt
공식 코드Pre-training Music Classification Models via Music Source Separation
https://github.com/cgcl-codes/advclip
공식 코드AdvCLIP: Downstream-agnostic Adversarial Examples in Multimodal Contrastive Learning
https://github.com/cgcl-codes/badhash
공식 코드BadHash: Invisible Backdoor Attacks against Deep Hashing with Clean Label
https://github.com/chakkritte/eeea-net
공식 코드EEEA-Net: An Early Exit Evolutionary Neural Architecture Search
https://github.com/chandar-lab/cmoptimizer
공식 코드Promoting Exploration in Memory-Augmented Adam using Critical Momenta
https://github.com/changchangsun/forget-vector
공식 코드https://github.com/changlin31/BossNAS
공식 코드https://github.com/changsn/STViT-R
공식 코드Making Vision Transformers Efficient from A Token Sparsification View
https://github.com/changwxx/csot-for-lnl
공식 코드CSOT: Curriculum and Structure-Aware Optimal Transport for Learning with Noisy Labels
https://github.com/chao1224/BadGlobalMinima
공식 코드https://github.com/chaomaer/FBSD
공식 코드Feature Boosting, Suppression, and Diversification for Fine-Grained Visual Classification
https://github.com/chaos96/fourierft
공식 코드Parameter-Efficient Fine-Tuning with Discrete Fourier Transform
https://github.com/charismaticchiu/Better-May-Not-Be-Fairer-A-Study-Study-on-Subgroup-Discrepancy-in-Image-Classification
공식 코드Better May Not Be Fairer: A Study on Subgroup Discrepancy in Image Classification
https://github.com/charismaticchiu/ddi-coco
공식 코드https://github.com/charles-xie/cql
공식 코드Category Query Learning for Human-Object Interaction Classification
https://github.com/charlesjin/compatibility_clustering
공식 코드Incompatibility Clustering as a Defense Against Backdoor Poisoning Attacks
https://github.com/charlesjin/synthetic_data
공식 코드https://github.com/charlotte-charmlab/fibottention
공식 코드Fibottention: Inceptive Visual Representation Learning with Diverse Attention Across Heads
https://github.com/charlotte-pel/temporalCNN
공식 코드Temporal Convolutional Neural Network for the Classification of Satellite Image Time Series
https://github.com/charmonyshen/firerisk
공식 코드https://github.com/cheerss/CrossFormer
공식 코드CrossFormer: A Versatile Vision Transformer Hinging on Cross-scale Attention
https://github.com/cheeun/odm
공식 코드Overcoming Distribution Mismatch in Quantizing Image Super-Resolution Networks
https://github.com/cheggan/metaaudio-a-few-shot-audio-classification-benchmark
공식 코드https://github.com/chehao2628/MSRN
공식 코드Multi-layered Semantic Representation Network for Multi-label Image Classification
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.