Papers with Code 아카이브

2D Classification

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

27

평가표

0

보존된 평가 기록

0

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/gaopengcuhk/SMCA-DETR

공식 코드

End-to-End Object Detection with Adaptive Clustering Transformer

https://github.com/gaoyingjay/ps-ttl

공식 코드

PS-TTL: Prototype-based Soft-labels and Test-Time Learning for Few-shot Object Detection

https://github.com/gap-lab-cuhk-sz/rec-mv

공식 코드

REC-MV: REconstructing 3D Dynamic Cloth from Monocular Videos

https://github.com/garfield-cpp/hgsfusion

공식 코드

HGSFusion: Radar-Camera Fusion with Hybrid Generation and Synchronization for 3D Object Detection

https://github.com/garrickbrazil/M3D-RPN

공식 코드

M3D-RPN: Monocular 3D Region Proposal Network for Object Detection

https://github.com/garyson1204/hginet

공식 코드

Hierarchical Graph Interaction Transformer with Dynamic Token Clustering for Camouflaged Object Detection

https://github.com/gatedip/gdip-yolo

공식 코드

GDIP: Gated Differentiable Image Processing for Object-Detection in Adverse Conditions

https://github.com/gatenlp/h3prompt

공식 코드

GateNLP at SemEval-2025 Task 10: Hierarchical Three-Step Prompting for Multilingual Narrative Classification

https://github.com/gatenlp/wordpress-site-extractor

공식 코드

Analysing State-Backed Propaganda Websites: a New Dataset and Linguistic Study

https://github.com/gatorsense/matl

공식 코드

Multi-Task Learning with Multi-Annotation Triplet Loss for Improved Object Detection

https://github.com/gauravreddy08/OcularAI

공식 코드

MagicEye: An Intelligent Wearable Towards Independent Living of Visually Impaired

https://github.com/gautamtata/DeepPlastic

공식 코드

A Robotic Approach towards Quantifying Epipelagic Bound Plastic Using Deep Visual Models

https://github.com/geoai-lab/EUPEG

공식 코드

Are We There Yet? Evaluating State-of-the-Art Neural Network based Geoparsers Using EUPEG as a Benchmarking Platform

https://github.com/geoffreychen777/vc

공식 코드

Semi-supervised Object Detection via Virtual Category Learning

https://github.com/geonhobang/RadarDistill

공식 코드

RadarDistill: Boosting Radar-based Object Detection Performance via Knowledge Distillation from LiDAR Features

https://github.com/georgeretsi/segfreekws

공식 코드

Keyword Spotting Simplified: A Segmentation-Free Approach using Character Counting and CTC re-scoring

https://github.com/georghess/neurad-studio

공식 코드

NeuRAD: Neural Rendering for Autonomous Driving

https://github.com/georghess/pmb-nll

공식 코드

Object Detection as Probabilistic Set Prediction

https://github.com/georghess/voxel-mae

공식 코드

Masked Autoencoder for Self-Supervised Pre-training on Lidar Point Clouds

https://github.com/georgia-tech-synergy-lab/clamp-vit

공식 코드

CLAMP-ViT: Contrastive Data-Free Learning for Adaptive Post-Training Quantization of ViTs

https://github.com/germanftv/parallaxicb

공식 코드

Depth-Aware Image Compositing Model for Parallax Camera Motion Blur

https://github.com/geshang777/FOCUS

공식 코드

FOCUS: Towards Universal Foreground Segmentation

https://github.com/geshang777/Seg-R1

공식 코드

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning

https://github.com/gewelsji/dgnet

공식 코드

Deep Gradient Learning for Efficient Camouflaged Object Detection

https://github.com/gewelsji/errnet

공식 코드

Fast Camouflaged Object Detection via Edge-based Reversible Re-calibration Network

https://github.com/gewu-lab/csol_tpami2021

공식 코드

Class-aware Sounding Objects Localization via Audiovisual Correspondence

https://github.com/gfxdisp/colorvideovdp

공식 코드

Training Neural Networks on RAW and HDR Images for Restoration Tasks

https://github.com/ggjy/DeFeat.pytorch

공식 코드

Distilling Object Detectors via Decoupled Features

https://github.com/ggjy/Hire-Wave-MLP.pytorch

공식 코드

Hire-MLP: Vision MLP via Hierarchical Rearrangement

https://github.com/ggjy/HitDet.pytorch

공식 코드

Hit-Detector: Hierarchical Trinity Architecture Search for Object Detection

https://github.com/ghostish/objectcentricocccompletion

공식 코드

Towards Flexible 3D Perception: Object-Centric Occupancy Completion Augments 3D Object Detection

https://github.com/giakoumoglou/synco

공식 코드

SynCo: Synthetic Hard Negatives in Contrastive Learning for Better Unsupervised Visual Representations

https://github.com/gicait/plitter

공식 코드

pLitterStreet: Street Level Plastic Litter Detection and Mapping

https://github.com/gidariss/AttractioNet

공식 코드

Attend Refine Repeat: Active Box Proposal Generation via In-Out Localization

https://github.com/gidariss/locnet

공식 코드

LocNet: Improving Localization Accuracy for Object Detection

https://github.com/gidariss/mrcnn-object-detection

공식 코드

Object detection via a multi-region & semantic segmentation-aware CNN model

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.