https://github.com/PaddlePaddle/Paddle3D
SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences
Papers with Code 아카이브
Scene Parsing
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Scene parsing is to segment and parse an image into different image regions associated with semantic categories, such as sky, road, person, and bed. MIT Description
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/PaddlePaddle/PaddleDetection
https://github.com/PaddlePaddle/PaddleVideo/blob/develop/docs/en/model_zoo/segmentation/cfbi.md
Collaborative Video Object Segmentation by Foreground-Background Integration
https://github.com/ParitoshParmar/HalluciNet--PyTorch
HalluciNet-ing Spatiotemporal Representations Using a 2D-CNN
https://github.com/PaulEmmanuelSotir/DeepCV
Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition
https://github.com/Paultool/segnet
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/Pay20Y/FOTS_TF
https://github.com/Pay20Y/SAR_TF
Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition
https://github.com/PhanTom2003/PSPnet
https://github.com/Pointcept/Pointcept
PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation
https://github.com/PratirupG/Handwriting-Recognition
https://github.com/PuchatekwSzortach/voc_fcn
https://github.com/QingyongHu/SQN
Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges
https://github.com/RTalha/CROWD-COUNTING-USING-CSRNET
CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes
https://github.com/RajkumarPreetham/Road-scene-understanding
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/Rintarooo/PSPNet
https://github.com/RituYadav92/Image-segmentation
https://github.com/RobotMobile/cv-deep-learning-paper-review
What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis
https://github.com/Rosie-Brigham/sesmeg
https://github.com/RuiZhou-cn/U3HS
Segmenting Known Objects and Unseen Unknowns without Prior Knowledge
https://github.com/RuijieZhu94/mmdepth
BinsFormer: Revisiting Adaptive Bins for Monocular Depth Estimation
https://github.com/RylanSchaeffer/prismatic-vlms
Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models
https://github.com/S-HuaBomb/MASTER-paddle
MASTER: Multi-Aspect Non-local Network for Scene Text Recognition
https://github.com/SSN15/Behavioral-Cloning--Implementaion-of-Autonomous-car-using-deep-learning
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/SYR-Aegis/BrailleOCR
https://github.com/SaifeddineBarkia/Multi-view-radar-semantic-segmentation-for-scene-understanding-in-autonomous-driving
https://github.com/SamvitJ/Accel
Accel: A Corrective Fusion Network for Efficient Semantic Segmentation on Video
https://github.com/Saritus/Crowd-Counter
CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes
https://github.com/Scalsol/mega.pytorch
https://github.com/Sentient07/HeadHunter-T
https://github.com/Shualite/SFNet.pytorch
https://github.com/Shun14/UperNet
https://github.com/ShunyuYao/blitznet_instance_segment
https://github.com/SilvioGiancola/SoccerNetv2-DevKit
SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos
https://github.com/SkyWa7ch3r/ImageSegmentation
https://github.com/SkyWa7ch3r/SceneSegmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.