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/mebzmoren/cebuaner

공식 코드

CebuaNER: A New Baseline Cebuano Named Entity Recognition Model

https://github.com/mecarill/2pcnet

공식 코드

2PCNet: Two-Phase Consistency Training for Day-to-Night Unsupervised Domain Adaptive Object Detection

https://github.com/med-air/endonerf

공식 코드

Neural Rendering for Stereo 3D Reconstruction of Deformable Tissues in Robotic Surgery

https://github.com/media-bias-analysis-group/neural-media-bias-detection-using-distant-supervision-with-babe

공식 코드

Neural Media Bias Detection Using Distant Supervision With BABE -- Bias Annotations By Experts

https://github.com/mediabrain-sjtu/mvfa-ad

공식 코드

Adapting Visual-Language Models for Generalizable Anomaly Detection in Medical Images

https://github.com/mediabrain-sjtu/where2comm

공식 코드

Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Maps

https://github.com/medicl-vu/crossmoda2023

공식 코드

Learning Site-specific Styles for Multi-institutional Unsupervised Cross-modality Domain Adaptation

https://github.com/meet-cjli/ctrl

공식 코드

An Embarrassingly Simple Backdoor Attack on Self-supervised Learning

https://github.com/megum1/beagle

공식 코드

BEAGLE: Forensics of Deep Learning Backdoor Attack for Better Defense

https://github.com/megum1/lotus

공식 코드

LOTUS: Evasive and Resilient Backdoor Attacks through Sub-Partitioning

https://github.com/megvii-basedetection/bevdepth

공식 코드

BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detection

https://github.com/megvii-basedetection/bevstereo

공식 코드

BEVStereo: Enhancing Depth Estimation in Multi-view 3D Object Detection with Dynamic Temporal Stereo

https://github.com/megvii-basedetection/denseteacher

공식 코드

Dense Teacher: Dense Pseudo-Labels for Semi-supervised Object Detection

https://github.com/megvii-model/CrowdDetection

공식 코드

Detection in Crowded Scenes: One Proposal, Multiple Predictions

https://github.com/megvii-model/DetNAS

공식 코드

DetNAS: Backbone Search for Object Detection

https://github.com/megvii-model/HINet

공식 코드

HINet: Half Instance Normalization Network for Image Restoration

https://github.com/megvii-model/LabelEnc

공식 코드

LabelEnc: A New Intermediate Supervision Method for Object Detection

https://github.com/megvii-model/MOTR

공식 코드

MOTR: End-to-End Multiple-Object Tracking with Transformer

https://github.com/megvii-model/YOLOF

공식 코드

You Only Look One-level Feature

https://github.com/megvii-model/anchordetr

공식 코드

Anchor DETR: Query Design for Transformer-Based Object Detection

https://github.com/megvii-model/iter-e2edet

공식 코드

Progressive End-to-End Object Detection in Crowded Scenes

https://github.com/megvii-research/AAAI2023-PVD

공식 코드

One is All: Bridging the Gap Between Neural Radiance Fields Architectures with Progressive Volume Distillation

https://github.com/megvii-research/AnchorDETR

공식 코드

Anchor DETR: Query Design for Transformer-Based Object Detection

https://github.com/megvii-research/ICD

공식 코드

Instance-Conditional Knowledge Distillation for Object Detection

https://github.com/megvii-research/LGD

공식 코드

LGD: Label-guided Self-distillation for Object Detection

https://github.com/megvii-research/NAFNet

공식 코드

Simple Baselines for Image Restoration

https://github.com/megvii-research/SOLQ

공식 코드

SOLQ: Segmenting Objects by Learning Queries

https://github.com/megvii-research/TLC

공식 코드

Improving Image Restoration by Revisiting Global Information Aggregation

https://github.com/megvii-research/co-mining

공식 코드

Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection

https://github.com/megvii-research/cvpr2023-unidistill

공식 코드

UniDistill: A Universal Cross-Modality Knowledge Distillation Framework for 3D Object Detection in Bird's-Eye View

https://github.com/megvii-research/dcls-sr

공식 코드

Deep Constrained Least Squares for Blind Image Super-Resolution

https://github.com/megvii-research/far3d

공식 코드

Far3D: Expanding the Horizon for Surround-view 3D Object Detection

https://github.com/megvii-research/mdistiller

공식 코드

Decoupled Knowledge Distillation

https://github.com/megvii-research/megactor

공식 코드

MegActor: Harness the Power of Raw Video for Vivid Portrait Animation

https://github.com/megvii-research/megfaceanimate

공식 코드

MegActor: Harness the Power of Raw Video for Vivid Portrait Animation

https://github.com/megvii-research/motr

공식 코드

MOTR: End-to-End Multiple-Object Tracking with Transformer

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