All Projects → improving_segmentation_with_selfsupervised_depth → Similar Projects or Alternatives

576 Open source projects that are alternatives of or similar to improving_segmentation_with_selfsupervised_depth

SPML
Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning
Stars: ✭ 81 (-57.14%)
Mutual labels:  semantic-segmentation
semantic-tsdf
Semantic-TSDF for Self-driving Static Scene Reconstruction
Stars: ✭ 14 (-92.59%)
Mutual labels:  semantic-segmentation
newt
Natural World Tasks
Stars: ✭ 24 (-87.3%)
Mutual labels:  self-supervised-learning
ssdg-benchmark
Benchmarks for semi-supervised domain generalization.
Stars: ✭ 46 (-75.66%)
Mutual labels:  semi-supervised-learning
map-floodwater-satellite-imagery
This repository focuses on training semantic segmentation models to predict the presence of floodwater for disaster prevention. Models were trained using SageMaker and Colab.
Stars: ✭ 21 (-88.89%)
Mutual labels:  semantic-segmentation
flexinfer
A flexible Python front-end inference SDK based on TensorRT
Stars: ✭ 83 (-56.08%)
Mutual labels:  semantic-segmentation
Summary-of-RGB-T-Salient-Object-Detection-and-Semantic-segmentation
Summary of RGBT SOD and SS.
Stars: ✭ 35 (-81.48%)
Mutual labels:  semantic-segmentation
deeplabv3plus-keras
deeplabv3plus (Google's new algorithm for semantic segmentation) in keras:Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
Stars: ✭ 67 (-64.55%)
Mutual labels:  semantic-segmentation
Dilation-Pytorch-Semantic-Segmentation
A PyTorch implementation of semantic segmentation according to Multi-Scale Context Aggregation by Dilated Convolutions by Yu and Koltun.
Stars: ✭ 32 (-83.07%)
Mutual labels:  semantic-segmentation
DualStudent
Code for Paper ''Dual Student: Breaking the Limits of the Teacher in Semi-Supervised Learning'' [ICCV 2019]
Stars: ✭ 106 (-43.92%)
Mutual labels:  semi-supervised-learning
G-SimCLR
This is the code base for paper "G-SimCLR : Self-Supervised Contrastive Learning with Guided Projection via Pseudo Labelling" by Souradip Chakraborty, Aritra Roy Gosthipaty and Sayak Paul.
Stars: ✭ 69 (-63.49%)
Mutual labels:  self-supervised-learning
esvit
EsViT: Efficient self-supervised Vision Transformers
Stars: ✭ 323 (+70.9%)
Mutual labels:  self-supervised-learning
cool-papers-in-pytorch
Reimplementing cool papers in PyTorch...
Stars: ✭ 21 (-88.89%)
Mutual labels:  semantic-segmentation
Semantic-Segmentation-BiSeNet
Keras BiseNet architecture implementation
Stars: ✭ 55 (-70.9%)
Mutual labels:  semantic-segmentation
deviation-network
Source code of the KDD19 paper "Deep anomaly detection with deviation networks", weakly/partially supervised anomaly detection, few-shot anomaly detection
Stars: ✭ 94 (-50.26%)
Mutual labels:  semi-supervised-learning
MobileUNET
U-NET Semantic Segmentation model for Mobile
Stars: ✭ 39 (-79.37%)
Mutual labels:  semantic-segmentation
plusseg
ShanghaiTech PLUS Lab Segmentation Toolbox and Benchmark
Stars: ✭ 21 (-88.89%)
Mutual labels:  semantic-segmentation
PhotographicImageSynthesiswithCascadedRefinementNetworks-Pytorch
Photographic Image Synthesis with Cascaded Refinement Networks - Pytorch Implementation
Stars: ✭ 63 (-66.67%)
Mutual labels:  semantic-segmentation
panoptic-forecasting
[CVPR 2021] Forecasting the panoptic segmentation of future video frames
Stars: ✭ 44 (-76.72%)
Mutual labels:  semantic-segmentation
AttaNet
AttaNet for real-time semantic segmentation.
Stars: ✭ 37 (-80.42%)
Mutual labels:  semantic-segmentation
recurrent-decoding-cell
[AAAI'20] Segmenting Medical MRI via Recurrent Decoding Cell (Spotlight)
Stars: ✭ 14 (-92.59%)
Mutual labels:  semantic-segmentation
awesome-graph-self-supervised-learning-based-recommendation
A curated list of awesome graph & self-supervised-learning-based recommendation.
Stars: ✭ 37 (-80.42%)
Mutual labels:  self-supervised-learning
Self-Supervised-Embedding-Fusion-Transformer
The code for our IEEE ACCESS (2020) paper Multimodal Emotion Recognition with Transformer-Based Self Supervised Feature Fusion.
Stars: ✭ 57 (-69.84%)
Mutual labels:  self-supervised-learning
semi-memory
Tensorflow Implementation on Paper [ECCV2018]Semi-Supervised Deep Learning with Memory
Stars: ✭ 49 (-74.07%)
Mutual labels:  semi-supervised-learning
BMW-Anonymization-API
This repository allows you to anonymize sensitive information in images/videos. The solution is fully compatible with the DL-based training/inference solutions that we already published/will publish for Object Detection and Semantic Segmentation.
Stars: ✭ 121 (-35.98%)
Mutual labels:  semantic-segmentation
SGDepth
[ECCV 2020] Self-Supervised Monocular Depth Estimation: Solving the Dynamic Object Problem by Semantic Guidance
Stars: ✭ 162 (-14.29%)
Mutual labels:  depth-estimation
collective-classification-weka-package
Semi-Supervised Learning and Collective Classification
Stars: ✭ 20 (-89.42%)
Mutual labels:  semi-supervised-learning
pytorch-segmentation
🎨 Semantic segmentation models, datasets and losses implemented in PyTorch.
Stars: ✭ 1,184 (+526.46%)
Mutual labels:  semantic-segmentation
InstantDL
InstantDL: An easy and convenient deep learning pipeline for image segmentation and classification
Stars: ✭ 33 (-82.54%)
Mutual labels:  semantic-segmentation
seededlda
Semisupervided LDA for theory-driven text analysis
Stars: ✭ 46 (-75.66%)
Mutual labels:  semi-supervised-learning
DeepAtlas
Joint Semi-supervised Learning of Image Registration and Segmentation
Stars: ✭ 38 (-79.89%)
Mutual labels:  semi-supervised-learning
self6dpp
Self6D++: Occlusion-Aware Self-Supervised Monocular 6D Object Pose Estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2021.
Stars: ✭ 45 (-76.19%)
Mutual labels:  self-supervised-learning
GrabCut-Annotation-Tool
OpenCVのGrabCut()を利用したセマンティックセグメンテーション向けアノテーションツール(Annotation tool using GrabCut() of OpenCV. It can be used to create datasets for semantic segmentation.)
Stars: ✭ 27 (-85.71%)
Mutual labels:  semantic-segmentation
Semi-Supervised-Learning-GAN
Semi-supervised Learning GAN
Stars: ✭ 72 (-61.9%)
Mutual labels:  semi-supervised-learning
SharpPeleeNet
ImageNet pre-trained SharpPeleeNet can be used in real-time Semantic Segmentation/Objects Detection
Stars: ✭ 13 (-93.12%)
Mutual labels:  semantic-segmentation
semantic-segmentation-tensorflow
Semantic segmentation task for ADE20k & cityscapse dataset, based on several models.
Stars: ✭ 84 (-55.56%)
Mutual labels:  semantic-segmentation
GeDML
Generalized Deep Metric Learning.
Stars: ✭ 30 (-84.13%)
Mutual labels:  self-supervised-learning
semantic-parsing-dual
Source code and data for ACL 2019 Long Paper ``Semantic Parsing with Dual Learning".
Stars: ✭ 17 (-91.01%)
Mutual labels:  semi-supervised-learning
BridgeDepthFlow
Bridging Stereo Matching and Optical Flow via Spatiotemporal Correspondence, CVPR 2019
Stars: ✭ 114 (-39.68%)
Mutual labels:  depth-estimation
Simple-does-it-weakly-supervised-instance-and-semantic-segmentation
Weakly Supervised Segmentation by Tensorflow. Implements semantic segmentation in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).
Stars: ✭ 46 (-75.66%)
Mutual labels:  semantic-segmentation
mmselfsup
OpenMMLab Self-Supervised Learning Toolbox and Benchmark
Stars: ✭ 2,315 (+1124.87%)
Mutual labels:  self-supervised-learning
BMW-IntelOpenVINO-Segmentation-Inference-API
This is a repository for a semantic segmentation inference API using the OpenVINO toolkit
Stars: ✭ 31 (-83.6%)
Mutual labels:  semantic-segmentation
unet-pytorch
This is the example implementation of UNet model for semantic segmentations
Stars: ✭ 17 (-91.01%)
Mutual labels:  semantic-segmentation
label-studio-frontend
Data labeling react app that is backend agnostic and can be embedded into your applications — distributed as an NPM package
Stars: ✭ 230 (+21.69%)
Mutual labels:  semantic-segmentation
TCE
This repository contains the code implementation used in the paper Temporally Coherent Embeddings for Self-Supervised Video Representation Learning (TCE).
Stars: ✭ 51 (-73.02%)
Mutual labels:  self-supervised-learning
JCLAL
JCLAL is a general purpose framework developed in Java for Active Learning.
Stars: ✭ 22 (-88.36%)
Mutual labels:  semi-supervised-learning
Lyft-Perception-Challenge
The 4th place and the fastest solution of the Lyft Perception Challenge (Image semantic segmentation with PyTorch)
Stars: ✭ 69 (-63.49%)
Mutual labels:  semantic-segmentation
generative models
Pytorch implementations of generative models: VQVAE2, AIR, DRAW, InfoGAN, DCGAN, SSVAE
Stars: ✭ 82 (-56.61%)
Mutual labels:  semi-supervised-learning
kitti deeplab
Inference script and frozen inference graph with fine tuned weights for semantic segmentation on images from the KITTI dataset.
Stars: ✭ 26 (-86.24%)
Mutual labels:  semantic-segmentation
SAFNet
[IROS 2021] Implementation of "Similarity-Aware Fusion Network for 3D Semantic Segmentation"
Stars: ✭ 19 (-89.95%)
Mutual labels:  semantic-segmentation
Dual-CNN-Models-for-Unsupervised-Monocular-Depth-Estimation
Dual CNN Models for Unsupervised Monocular Depth Estimation
Stars: ✭ 36 (-80.95%)
Mutual labels:  depth-estimation
project-defude
Refocus an image just by clicking on it with no additional data
Stars: ✭ 69 (-63.49%)
Mutual labels:  depth-estimation
CVPR21 PASS
PyTorch implementation of our CVPR2021 (oral) paper "Prototype Augmentation and Self-Supervision for Incremental Learning"
Stars: ✭ 55 (-70.9%)
Mutual labels:  self-supervised-learning
awesome-graph-self-supervised-learning
Awesome Graph Self-Supervised Learning
Stars: ✭ 805 (+325.93%)
Mutual labels:  self-supervised-learning
deepOF
TensorFlow implementation for "Guided Optical Flow Learning"
Stars: ✭ 26 (-86.24%)
Mutual labels:  semi-supervised-learning
MSF
Official code for "Mean Shift for Self-Supervised Learning"
Stars: ✭ 42 (-77.78%)
Mutual labels:  self-supervised-learning
LinkNet tensorflow
TensorFlow implementation of LinkNet
Stars: ✭ 16 (-91.53%)
Mutual labels:  semantic-segmentation
MINet
Multi-scale Interaction for Real-time LiDAR Data Segmentation on an Embedded Platform (RA-L)
Stars: ✭ 28 (-85.19%)
Mutual labels:  semantic-segmentation
night image semantic segmentation
[ICIP 2019] : This is the official github repository for the paper "What's There in The Dark" accepted in IEEE International Conference in Image Processing 2019 (ICIP19) , Taipei, Taiwan.
Stars: ✭ 25 (-86.77%)
Mutual labels:  semantic-segmentation
video repres mas
code for CVPR-2019 paper: Self-supervised Spatio-temporal Representation Learning for Videos by Predicting Motion and Appearance Statistics
Stars: ✭ 63 (-66.67%)
Mutual labels:  self-supervised-learning
61-120 of 576 similar projects