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/cavedunissin/deeplearning_robot_jetson_nano

Going Deeper with Convolutions

https://github.com/ccc013/DeepLearning_Notes

The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale

https://github.com/ccchang1023/maskrcnn-benchmark

RetinaMask: Learning to predict masks improves state-of-the-art single-shot detection for free

https://github.com/cdluminate/advrank

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/cdluminate/advrank-pub

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/cdoersch/deepcontext

Data-dependent Initializations of Convolutional Neural Networks

https://github.com/cds-mipt/cds-tracking

FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking

https://github.com/cedricpicron/detseg

Trident Pyramid Networks: The importance of processing at the feature pyramid level for better object detection

https://github.com/ceesem/refid2bib

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/celinechanny/FV-UPatches

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/cersar/3D_detection

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/cfdoge/w9ai

SSD: Single Shot MultiBox Detector

https://github.com/cfreshgirl/hardnet

HarDNet: A Low Memory Traffic Network

https://github.com/cftang0827/human_recognition

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/cftang0827/pedestrian-detection-ssdlite

Rich feature hierarchies for accurate object detection and semantic segmentation

https://github.com/cftang0827/pedestrian_detection_ssdlite

Rich feature hierarchies for accurate object detection and semantic segmentation

https://github.com/cftang0827/pedestrian_recognition

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/cg1177/dcan

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

https://github.com/cgebbe/kaggle_pku-autonomous-driving

MnasNet: Platform-Aware Neural Architecture Search for Mobile

https://github.com/chainer/chainercv

ChainerCV: a Library for Deep Learning in Computer Vision

https://github.com/chakerouari/UNET_segmetation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/chandra411/Product-Detection

SSD: Single Shot MultiBox Detector

https://github.com/chandrikadeb7/face-mask-detection

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/changliu816/CV-paper-review

Non-local Neural Networks

https://github.com/chanlilong/4D_NET_pytorch

4D-Net for Learned Multi-Modal Alignment

https://github.com/chaowang1994/caffe-ssd

SSD: Single Shot MultiBox Detector

https://github.com/charlesCXK/RGBD_Semantic_Segmentation_PyTorch

Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation

https://github.com/charlesYangM/py-faster-rcnn-80.28

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

https://github.com/charlescxk/depth2hha-python

Learning Rich Features from RGB-D Images for Object Detection and Segmentation

https://github.com/charlesq34/pointnet

Frustum PointNets for 3D Object Detection from RGB-D Data

https://github.com/charlesq34/pointnet2

Frustum PointNets for 3D Object Detection from RGB-D Data

https://github.com/charlesshang/fastmaskrcnn

Mask R-CNN

https://github.com/charlychiu/U-Net

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/chartgalaxy/chartgalaxy

OrionBench: A Benchmark for Chart and Human-Recognizable Object Detection in Infographics

https://github.com/chayanchatterjee/cbc-skynet

Deep Residual Learning for Image Recognition

https://github.com/chayanchatterjee/gw-skylocator

Deep Residual Learning for Image Recognition

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