Papers with Code 아카이브

Scene Parsing

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전체 기법 전체 데이터셋

하위 태스크: 9
평가표: 2
보존된 평가 기록: 3

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/MindCode-4/code-5/tree/main/trocr

TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models

https://github.com/MindCode-4/code-5/tree/main/upernet

Unified Perceptual Parsing for Scene Understanding

https://github.com/MindCode-4/code-5/tree/main/videomae

Unified Perceptual Parsing for Scene Understanding

https://github.com/MindCode-4/code-6/tree/main/auxiliary-tasks-in-multi-task-learning

Auxiliary Tasks in Multi-task Learning

https://github.com/MindSpore-paper-code-2/code2/tree/main/OSVOS

Make One-Shot Video Object Segmentation Efficient Again

https://github.com/MindSpore-paper-code-2/code2/tree/main/PSPNet

Pyramid Scene Parsing Network

https://github.com/MindSpore-paper-code-3/code1/tree/main/AttGAN

High Resolution Face Editing with Masked GAN Latent Code Optimization

https://github.com/MindSpore-paper-code-3/code10/tree/main/FCN8s

Fully Convolutional Networks for Semantic Segmentation

https://github.com/MindSpore-paper-code-3/code2/tree/main/DDRNet

Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes

https://github.com/MindSpore-paper-code-3/code8/tree/main/DDRNet

Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes

https://github.com/MindSpore-paper-code-3/code8/tree/main/dlinknet

LinkNet: Relational Embedding for Scene Graph

https://github.com/MindSpore-scientific-2/code-14/tree/main/groupvit

GroupViT: Semantic Segmentation Emerges from Text Supervision

https://github.com/MindSpore-scientific-2/code-2/tree/main/Super-Resolution-for-Root-Imaging

ROOT: VLM based System for Indoor Scene Understanding and Beyond

https://github.com/MindSpore-scientific-2/code-5/tree/main/Luminance-Guided-Chrominance-Enhancement-for-HEVC-Intra-Coding

LUMINOUS: Indoor Scene Generation for Embodied AI Challenges

https://github.com/MindSpore-scientific/code-1/tree/main/Luminance-Guided-Chrominance-Enhancement-for-HEVC-Intra-Coding

LUMINOUS: Indoor Scene Generation for Embodied AI Challenges

https://github.com/MindSpore-scientific/code-10/tree/main/Luminance-Guided-Chrominance-Enhancement-for-HEVC-Intra-Coding

LUMINOUS: Indoor Scene Generation for Embodied AI Challenges

https://github.com/MindSpore-scientific/code-10/tree/main/Super-Resolution-for-Root-Imaging

ROOT: VLM based System for Indoor Scene Understanding and Beyond

https://github.com/MindSpore-scientific/code-14/tree/main/SGDR

SGDraw: Scene Graph Drawing Interface Using Object-Oriented Representation

https://github.com/MindSpore-scientific/code-5/tree/main/SGDR

SGDraw: Scene Graph Drawing Interface Using Object-Oriented Representation

https://github.com/MindSpore-scientific/code-7/tree/main/SAM

SAM 2: Segment Anything in Images and Videos

https://github.com/MindSpore-scientific/code-7/tree/main/UPerNet

Unified Perceptual Parsing for Scene Understanding

https://github.com/Mingtzge/2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/ModelBunker/MORAN-PyTorch

A Multi-Object Rectified Attention Network for Scene Text Recognition

https://github.com/MuchHair/PD-Net-Extended-Version

Polysemy Deciphering Network for Robust Human-Object Interaction Detection

https://github.com/NVlabs/neuralrgbd

Neural RGB->D Sensing: Depth and Uncertainty from a Video Camera

https://github.com/Narp99/FRI_2018

STN-OCR: A single Neural Network for Text Detection and Text Recognition

https://github.com/Neerajj9/CSRNet-keras

CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

https://github.com/NeuronDroid/GVSS-S.A.Drone

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

https://github.com/NiallEHunt/MonocularDepth-Using-LightFields

Digging Into Self-Supervised Monocular Depth Estimation

https://github.com/Nicholasli1995/EgoNet

M3D-RPN: Monocular 3D Region Proposal Network for Object Detection

https://github.com/NikolasEnt/soccernet-calibration-sportlight

SoccerNet 2023 Challenges Results

https://github.com/OneYearIsEnough/PaddleOCR-Recog-LmdbDataset-Conversion

Primitive Representation Learning for Scene Text Recognition

https://github.com/OpenNeuroDatasets/ds001499

BOLD5000: A public fMRI dataset of 5000 images

https://github.com/Osdel/ssnets

Fully Convolutional Networks for Semantic Segmentation

https://github.com/OzHsu23/chineseocr

COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural Images

https://github.com/PRBonn/bonnet

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.