Papers with Code 아카이브
Scene Parsing
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
- 2
- 보존된 평가 기록
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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/Srijan2001/Keypoint-regression
https://github.com/StanLei52/GEBD
Generic Event Boundary Detection: A Benchmark for Event Segmentation
https://github.com/SunDaDenny/DuLa-Net
DuLa-Net: A Dual-Projection Network for Estimating Room Layouts from a Single RGB Panorama
https://github.com/T-a-g-z/Yotube-VOS-OVS
https://github.com/TWJianNuo/panoptic-scene-understanding
https://github.com/TanyaChutani/Monodepth-Tf2.x
https://github.com/Tashnim-Chowdhury/FloodNet-Challenge-EARTHVISION2021
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding
https://github.com/TejasBajania/Mtech_pro
https://github.com/TejasBajania/Mtech_thesis_project
https://github.com/Tez01/SegNet-Keras-Implementation
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/TheUser0815/segnet-pytorch
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/TimoSaemann/caffe-segnet-cudnn5
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/TingdiRen/URSCT-SESR
Underwater Image Super-Resolution using Deep Residual Multipliers
https://github.com/TqDavid/td
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/TracelessLe/FaceParsing.PyTorch
https://github.com/TranThienDat-Nguyen/VisionEvaluation
https://github.com/TripleJoy/SAM2MOT
https://github.com/Turoad/lanedet
Spatial As Deep: Spatial CNN for Traffic Scene Understanding
https://github.com/UBC-CIC/COVID19-L3-Net
https://github.com/UCB-ICSI-Vision-Group/decaf-release
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
https://github.com/UCBAIR/decaf-release
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
https://github.com/VCL3D/DeepPanoramaLighting
Deep Lighting Environment Map Estimation from Spherical Panoramas
https://github.com/VICO-UoE/KD4MTL
https://github.com/VamosC/CLIP4STR
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model
https://github.com/VenkatNarayanan11/Semantic-Segmentation_Autonomous-Wheelchair
https://github.com/Violet981/Breast_mass_Segmentation
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/VisualAnalysisOfHumans/LOVEU_TRACK1_TOP3_SUBMISSION
Generic Event Boundary Detection: A Benchmark for Event Segmentation
https://github.com/VisualComputingInstitute/mots_trackingonly_tools
PReMVOS: Proposal-generation, Refinement and Merging for Video Object Segmentation
https://github.com/WarBean/tps_stn_pytorch
https://github.com/WenmuZhou/PytorchOCR
https://github.com/WenmuZhou/Segmentation-Free_OCR
https://github.com/WenmuZhou/crnn.pytorch
https://github.com/Whiffe/mmaction2_YF
Rethinking Self-supervised Correspondence Learning: A Video Frame-level Similarity Perspective
https://github.com/XXXVincent/MonoDepth2
https://github.com/XiangbingJi/Stanford-cs230-final-project
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.