Papers with Code 아카이브

Object Detection

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하위 태스크

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평가표

124

보존된 평가 기록

977

코드

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

https://github.com/leondgarse/keras_cv_attention_models/tree/main/keras_cv_attention_models/yolox

YOLOX: Exceeding YOLO Series in 2021

https://github.com/leot13/BarlowTwins

Barlow Twins: Self-Supervised Learning via Redundancy Reduction

https://github.com/lessw2020/auto-adaptive-ai

Micro-Batch Training with Batch-Channel Normalization and Weight Standardization

https://github.com/lessw2020/mish

Mish: A Self Regularized Non-Monotonic Activation Function

https://github.com/levindabhi/cloth-segmentation

U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection

https://github.com/lewandofskee/MobileMamba

Rethinking Atrous Convolution for Semantic Image Segmentation

https://github.com/lhaof/Salient-Object-Detection-Papers

Reverse Attention for Salient Object Detection

https://github.com/lhaof/fast-salient-object-detection

Reverse Attention for Salient Object Detection

https://github.com/lhcezx/Graph-FPN

Focal Loss for Dense Object Detection

https://github.com/lhwcv/mlsd_pytorch

Towards Light-weight and Real-time Line Segment Detection

https://github.com/lhwcv/mmdet

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/li-yibing/oceannet

YOLO9000: Better, Faster, Stronger

https://github.com/liang-faan/openpose

Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/liangfu/mxnet-mobilenet-v2

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/liangheming/faster_rcnnv1

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

https://github.com/liangheming/sparse_rcnnv1

Sparse R-CNN: End-to-End Object Detection with Learnable Proposals

https://github.com/libeineu/mmt-vqa

On Vision Features in Multimodal Machine Translation

https://github.com/libffcv/ffcv-imagenet

Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints

https://github.com/libiseller/MobileNetV2-dynamicFPN

Feature Pyramid Networks for Object Detection

https://github.com/lichengunc/mask-faster-rcnn

Mask R-CNN

https://github.com/lichuanqi/YOLOV4_Darknet

YOLOv3: An Incremental Improvement

https://github.com/lidio601/node-facedetect-supyo

Object Detection with Pixel Intensity Comparisons Organized in Decision Trees

https://github.com/lifebeyondexpectations/eccv22-pointmixer

Point Transformer

https://github.com/lifuguan/SOLOv2-mmdet

SOLOv2: Dynamic and Fast Instance Segmentation

https://github.com/lifuguan/UPDETR-mmdet

UP-DETR: Unsupervised Pre-training for Object Detection with Transformers

https://github.com/ligaoqi2/Pose2Seg-single-person-video-demo

Pose2Seg: Detection Free Human Instance Segmentation

https://github.com/ligaripash/KWtQ-face-alignment

TransTrack: Multiple Object Tracking with Transformer

https://github.com/lightly-ai/lightly

Dense Contrastive Learning for Self-Supervised Visual Pre-Training

https://github.com/liguolinhit/DynaSLAM

DynaSLAM: Tracking, Mapping and Inpainting in Dynamic Scenes

https://github.com/lijain/FCOS-change

FCOS: Fully Convolutional One-Stage Object Detection

https://github.com/lijiaman/CASENet

CASENet: Deep Category-Aware Semantic Edge Detection

https://github.com/liketheflower/yonod

simCrossTrans: A Simple Cross-Modality Transfer Learning for Object Detection with ConvNets or Vision Transformers

https://github.com/lilanxiao/Rotated_IoU

IoU Loss for 2D/3D Object Detection

https://github.com/lilanxiao/invar3d

A Closer Look at Invariances in Self-supervised Pre-training for 3D Vision

https://github.com/lilin19890401/FairMOT

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

https://github.com/lilujunai/emq-series

BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction

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