Papers with Code 아카이브

Object

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Replace the cat with a British Shorthair cat of the breed with bulging yellow eyes

코드

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

https://github.com/krish-thorcode/Object-Recognition

Striving for Simplicity: The All Convolutional Net

https://github.com/kritiksoman/GIMP-ML

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/krstevskipetar/SSDLite320-MobileNetV3-object-detection

SSD: Single Shot MultiBox Detector

https://github.com/krullgit/realsense_3d_detection

PointPillars: Fast Encoders for Object Detection from Point Clouds

https://github.com/krumo/Detectron-DA-Faster-RCNN

Domain Adaptive Faster R-CNN for Object Detection in the Wild

https://github.com/krumo/Domain-Adaptive-Faster-RCNN-PyTorch

Domain Adaptive Faster R-CNN for Object Detection in the Wild

https://github.com/ksheeraj/CS256-AI-ObjectDetection

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

https://github.com/kshmelkov/incremental_detectors

Incremental Learning of Object Detectors without Catastrophic Forgetting

https://github.com/ktlhtn/AutoSTAnnot

Object Detection in Equirectangular Panorama

https://github.com/kuangliu/pytorch-fpn

Feature Pyramid Networks for Object Detection

https://github.com/kujason/ip_basic

Joint 3D Proposal Generation and Object Detection from View Aggregation

https://github.com/kuku-sichuan/CenterNet

CenterNet: Keypoint Triplets for Object Detection

https://github.com/kunal-visoulia/Object-Recognition-Using-CNN

Striving for Simplicity: The All Convolutional Net

https://github.com/kushaswani/LitterNet-webapp

EfficientDet: Scalable and Efficient Object Detection

https://github.com/kvijaykrish/Bosch_AI_VehicleClassification

YOLO9000: Better, Faster, Stronger

https://github.com/kwai-kolors/kolors

DragAnything: Motion Control for Anything using Entity Representation

https://github.com/kyegomez/PALI

PaLI-X: On Scaling up a Multilingual Vision and Language Model

https://github.com/kyegomez/RT-2

RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control

https://github.com/kyscg/tf-models

Mobile Video Object Detection with Temporally-Aware Feature Maps

https://github.com/kyunghwan/darknet_v3

YOLO9000: Better, Faster, Stronger

https://github.com/kyungsu-lee-ksl/ash

Microsoft COCO: Common Objects in Context

https://github.com/labmlai/annotated_deep_learning_paper_implementations

Group Normalization

https://github.com/laclouis5/darknet2

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/lahaproject/inavit

Interaction Region Visual Transformer for Egocentric Action Anticipation

https://github.com/lalithjets/domain-adaptation-in-mtl

Visual-Semantic Graph Attention Networks for Human-Object Interaction Detection

https://github.com/lalithjets/domain-generalization-for-surgical-scene-graph

Visual-Semantic Graph Attention Networks for Human-Object Interaction Detection

https://github.com/lalithjets/global-reasoned-multi-task-model

Visual-Semantic Graph Attention Networks for Human-Object Interaction Detection

https://github.com/lalonderodney/SegCaps

Capsules for Object Segmentation

https://github.com/lampsonSong/tinySSD

Tiny SSD: A Tiny Single-shot Detection Deep Convolutional Neural Network for Real-time Embedded Object Detection

https://github.com/lanPN85/HarDNet-MSEG

HarDNet-MSEG: A Simple Encoder-Decoder Polyp Segmentation Neural Network that Achieves over 0.9 Mean Dice and 86 FPS

https://github.com/lanmei1211/face

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/lanqingl/scs

Salient Object-Aware Background Generation using Text-Guided Diffusion Models

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

FCOS: Fully Convolutional One-Stage Object Detection

https://github.com/laycoding/FaceDetection

Single-Shot Refinement Neural Network for Object Detection

https://github.com/laycoding/PostiveDet

Single-Shot Refinement Neural Network for Object Detection

https://github.com/laycoding/renlianjiance

Single-Shot Refinement Neural Network for Object Detection

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