Papers with Code 아카이브

Object Detection

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

39

평가표

124

보존된 평가 기록

977

코드

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

https://github.com/matheusbarrosp/chessmix

공식 코드

ChessMix: Spatial Context Data Augmentation for Remote Sensing Semantic Segmentation

https://github.com/mathlee/acconet

공식 코드

Adjacent Context Coordination Network for Salient Object Detection in Optical Remote Sensing Images

https://github.com/mathlee/corrnet

공식 코드

Lightweight Salient Object Detection in Optical Remote Sensing Images via Feature Correlation

https://github.com/mathlee/gelenet

공식 코드

Salient Object Detection in Optical Remote Sensing Images Driven by Transformer

https://github.com/mathlee/mccnet

공식 코드

Multi-Content Complementation Network for Salient Object Detection in Optical Remote Sensing Images

https://github.com/mathlee/seanet

공식 코드

Lightweight Salient Object Detection in Optical Remote-Sensing Images via Semantic Matching and Edge Alignment

https://github.com/mathlee/tscnet

공식 코드

Texture-Semantic Collaboration Network for ORSI Salient Object Detection

https://github.com/matonima/lightweight-classifier/blob/main/TPA.py

공식 코드

Auto-Detection of Tibial Plateau Angle in Canine Radiographs Using a Deep Learning Approach

https://github.com/mattiasegu/darth

공식 코드

DARTH: Holistic Test-time Adaptation for Multiple Object Tracking

https://github.com/maubreville/MitosisRegionOfInterest

공식 코드

Deep learning algorithms out-perform veterinary pathologists in detecting the mitotically most active tumor region

https://github.com/maups/covid19-satellite-analysis

공식 코드

Measuring Human and Economic Activity from Satellite Imagery to Support City-Scale Decision-Making during COVID-19 Pandemic

https://github.com/maxiuw/uada3d

공식 코드

UADA3D: Unsupervised Adversarial Domain Adaptation for 3D Object Detection with Sparse LiDAR and Large Domain Gaps

https://github.com/maycbj/dit

공식 코드

DiT: Efficient Vision Transformers with Dynamic Token Routing

https://github.com/mayechi/lt3d-lf

공식 코드

Long-Tailed 3D Detection via Multi-Modal Fusion

https://github.com/mayu-ot/oc-cost

공식 코드

Optimal Correction Cost for Object Detection Evaluation

https://github.com/mazurowski-lab/breastMRI_styletransfer

공식 코드

Deep Learning for Breast MRI Style Transfer with Limited Training Data

https://github.com/mbar0075/object-detection-correlation-saliency-vs-depth

공식 코드

Correlation of Object Detection Performance with Visual Saliency and Depth Estimation

https://github.com/mbar0075/sarlvision

공식 코드

Integrating Saliency Ranking and Reinforcement Learning for Enhanced Object Detection

https://github.com/mcahny/object_localization_network

공식 코드

Learning Open-World Object Proposals without Learning to Classify

https://github.com/mcahny/rovit

공식 코드

Region-Aware Pretraining for Open-Vocabulary Object Detection with Vision Transformers

https://github.com/mcg-nju/adamixer

공식 코드

AdaMixer: A Fast-Converging Query-Based Object Detector

https://github.com/mcg-nju/basictad

공식 코드

BasicTAD: an Astounding RGB-Only Baseline for Temporal Action Detection

https://github.com/mcg-nju/deqdet

공식 코드

Deep Equilibrium Object Detection

https://github.com/mcg-nju/link

공식 코드

LinK: Linear Kernel for LiDAR-based 3D Perception

https://github.com/mcg-nju/logn

공식 코드

Logit Normalization for Long-tail Object Detection

https://github.com/mcg-nju/sparsebev

공식 코드

SparseBEV: High-Performance Sparse 3D Object Detection from Multi-Camera Videos

https://github.com/mcg-nju/stageinteractor

공식 코드

StageInteractor: Query-based Object Detector with Cross-stage Interaction

https://github.com/mcg-nju/structured-sparse-rcnn

공식 코드

Structured Sparse R-CNN for Direct Scene Graph Generation

https://github.com/mcg-nju/tia

공식 코드

Task-specific Inconsistency Alignment for Domain Adaptive Object Detection

https://github.com/mcv-m6-video/mcv-m6-2021-team4

공식 코드

Video Surveillance for Road Traffic Monitoring

https://github.com/mczhuge/ICON

공식 코드

Salient Object Detection via Integrity Learning

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

공식 코드

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

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

공식 코드

Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Maps

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

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