Papers with Code 아카이브

2D Object Detection

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

15

평가표

20

보존된 평가 기록

57

코드

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

https://github.com/k-h-ismail/convnext-dcls

공식 코드

Dilated convolution with learnable spacings

https://github.com/k-h-ismail/dilated-convolution-with-learnable-spacings-pytorch

공식 코드

Dilated convolution with learnable spacings

https://github.com/k-radlak/IDCNN

공식 코드

Deep Learning based Switching Filter for Impulsive Noise Removal in Color Images

https://github.com/k2okoh/mad

공식 코드

Multi-view Adversarial Discriminator: Mine the Non-causal Factors for Object Detection in Unseen Domains

https://github.com/k4ntz/moc

공식 코드

Boosting Object Representation Learning via Motion and Object Continuity

https://github.com/ka-mirul/r-sparse-r-cnn

공식 코드

R-Sparse R-CNN: SAR Ship Detection Based on Background-Aware Sparse Learnable Proposals

https://github.com/kahroba2000/biogan

공식 코드

BioGAN: An unpaired GAN-based image to image translation model for microbiological images

https://github.com/kai3316/yolic-labeling

공식 코드

YOLIC: An Efficient Method for Object Localization and Classification on Edge Devices

https://github.com/kailigo/cddod

공식 코드

Cross-Domain Document Object Detection: Benchmark Suite and Method

https://github.com/kaist-avelab/k-radar

공식 코드

K-Radar: 4D Radar Object Detection for Autonomous Driving in Various Weather Conditions

https://github.com/kaixinbear/CAPE

공식 코드

CAPE: Camera View Position Embedding for Multi-View 3D Object Detection

https://github.com/kakaobrain/HOTR

공식 코드

HOTR: End-to-End Human-Object Interaction Detection with Transformers

https://github.com/kakaobrain/solvent

공식 코드

Solvent: A Framework for Protein Folding

https://github.com/kakaobrain/sparse-detr

공식 코드

Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity

https://github.com/kakashiz/nedb-net

공식 코드

Noise and Edge Based Dual Branch Image Manipulation Detection

https://github.com/kancharlavamshi/icip2023_challenge

공식 코드

Overcoming Scene Context Constraints for Object Detection in wild using Defilters

https://github.com/kangliao929/cylin-painting

공식 코드

Cylin-Painting: Seamless {360\textdegree} Panoramic Image Outpainting and Beyond

https://github.com/karttikeya/minrev

공식 코드

Reversible Vision Transformers

https://github.com/kau-quantumailab/rfpar

공식 코드

Amnesia as a Catalyst for Enhancing Black Box Pixel Attacks in Image Classification and Object Detection

https://github.com/kbui1993/NonconvexNetworkSlimming

공식 코드

Improving Network Slimming with Nonconvex Regularization

https://github.com/kcl-bmeis/ultraflwr

공식 코드

UltraFlwr -- An Efficient Federated Medical and Surgical Object Detection Framework

https://github.com/kcyu2014/lidar-camera-robust-benchmark

공식 코드

Benchmarking the Robustness of LiDAR-Camera Fusion for 3D Object Detection

https://github.com/kdexd/coco-rem

공식 코드

Benchmarking Object Detectors with COCO: A New Path Forward

https://github.com/kdexd/virtex

공식 코드

VirTex: Learning Visual Representations from Textual Annotations

https://github.com/keenyjin/soia-dod

공식 코드

Short-term Object Interaction Anticipation with Disentangled Object Detection @ Ego4D Short Term Object Interaction Anticipation Challenge

https://github.com/kemaloksuz/BoundingBoxGenerator

공식 코드

Generating Positive Bounding Boxes for Balanced Training of Object Detectors

https://github.com/kemaloksuz/LRP-Error

공식 코드

One Metric to Measure them All: Localisation Recall Precision (LRP) for Evaluating Visual Detection Tasks

https://github.com/kemaloksuz/ObjectDetectionImbalance

공식 코드

Imbalance Problems in Object Detection: A Review

https://github.com/kemaloksuz/RankSortLoss

공식 코드

Rank & Sort Loss for Object Detection and Instance Segmentation

https://github.com/kemaloksuz/aLRPLoss

공식 코드

A Ranking-based, Balanced Loss Function Unifying Classification and Localisation in Object Detection

https://github.com/kemo-huang/jmodt

공식 코드

Joint Multi-Object Detection and Tracking with Camera-LiDAR Fusion for Autonomous Driving

https://github.com/kentaroy47/DatasetCulling

공식 코드

Dataset Culling: Towards Efficient Training Of Distillation-Based Domain Specific Models

https://github.com/kentaroy47/training-domain-specific-models

공식 코드

Training Domain Specific Models for Energy-Efficient Object Detection

https://github.com/kerenfu/JLDCF

공식 코드

JL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object Detection

https://github.com/kerenfu/LFSOD-Survey

공식 코드

Light Field Salient Object Detection: A Review and Benchmark

https://github.com/kerenfu/rdvs

공식 코드

Salient Object Detection in RGB-D Videos

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