How to Generate Synthetic Tabular Dataset
https://www.kdnuggets.com/2022/03/generate-tabular-synthetic-dataset.html
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https://www.kdnuggets.com/2022/03/generate-tabular-synthetic-dataset.html
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💬 A Text Attention Network for Spatial Deformation Robust Scene Text Image Super-resolution
Github: https://github.com/mjq11302010044/tatt
Paper: https://arxiv.org/abs/2203.09388v2
Dataset: https://deepchecks.com/blog/
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Github: https://github.com/mjq11302010044/tatt
Paper: https://arxiv.org/abs/2203.09388v2
Dataset: https://deepchecks.com/blog/
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〰 Monotonic Differentiable Sorting Networks
Github: https://github.com/Felix-Petersen/diffsort
Colab: https://colab.research.google.com/drive/1q0TZFFYB9FlOJYWKt0_7ZaXQT190anhm?usp=sharing
Paper: https://arxiv.org/abs/2203.09630v1
Video: https://www.youtube.com/watch?v=Rl-sFaE1z4M
Dataset: https://paperswithcode.com/dataset/svhn
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Github: https://github.com/Felix-Petersen/diffsort
Colab: https://colab.research.google.com/drive/1q0TZFFYB9FlOJYWKt0_7ZaXQT190anhm?usp=sharing
Paper: https://arxiv.org/abs/2203.09630v1
Video: https://www.youtube.com/watch?v=Rl-sFaE1z4M
Dataset: https://paperswithcode.com/dataset/svhn
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⚡️ EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation
Article
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Article
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Дзен | Статьи
Машинное обучение
Пост автора «Машинное обучение» в Дзене ✍: ⚡️ EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation Github: https://github.
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💭 NeuralSpeech is a research project in focusing on neural network based speech processing
Github: https://github.com/microsoft/NeuralSpeech
Paper: https://arxiv.org/pdf/2109.14420v3.pdf
Speech Research: https://speechresearch.github.io/
Dataset: https://paperswithcode.com/dataset/aishell-1
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Github: https://github.com/microsoft/NeuralSpeech
Paper: https://arxiv.org/pdf/2109.14420v3.pdf
Speech Research: https://speechresearch.github.io/
Dataset: https://paperswithcode.com/dataset/aishell-1
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🔎 BigDetection: A Large-scale Benchmark for Improved Object Detector Pre-training
Github: https://github.com/amazon-research/bigdetection
Paper: https://arxiv.org/abs/2203.13249v1
Dataset: https://paperswithcode.com/dataset/lvis
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Github: https://github.com/amazon-research/bigdetection
Paper: https://arxiv.org/abs/2203.13249v1
Dataset: https://paperswithcode.com/dataset/lvis
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🎨 Autoregressive Image Generation using Residual Quantization
Github: https://github.com/kakaobrain/rq-vae-transformer
Pytorch: https://github.com/lucidrains/vector-quantize-pytorch
Paper: https://arxiv.org/abs/2203.01941v2
Dataset: https://paperswithcode.com/dataset/lsun
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Github: https://github.com/kakaobrain/rq-vae-transformer
Pytorch: https://github.com/lucidrains/vector-quantize-pytorch
Paper: https://arxiv.org/abs/2203.01941v2
Dataset: https://paperswithcode.com/dataset/lsun
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GitHub
GitHub - kakaobrain/rq-vae-transformer: The official implementation of Autoregressive Image Generation using Residual Quantization…
The official implementation of Autoregressive Image Generation using Residual Quantization (CVPR '22) - kakaobrain/rq-vae-transformer
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🎨 Pastiche Master: Exemplar-Based High-Resolution Portrait Style Transfer
Github: https://github.com/williamyang1991/DualStyleGAN
Paper: https://arxiv.org/abs/2203.13248v1
Video: https://www.youtube.com/watch?v=scZTu77jixI
Project: https://www.mmlab-ntu.com/project/dualstylegan/
Dataset: https://paperswithcode.com/dataset/ffhq
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Github: https://github.com/williamyang1991/DualStyleGAN
Paper: https://arxiv.org/abs/2203.13248v1
Video: https://www.youtube.com/watch?v=scZTu77jixI
Project: https://www.mmlab-ntu.com/project/dualstylegan/
Dataset: https://paperswithcode.com/dataset/ffhq
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🤖 REGTR: End-to-end Point Cloud Correspondences with Transformers
Github: https://github.com/yewzijian/regtr
Paper: https://arxiv.org/abs/2203.14517v1
Pretrained models: https://github.com/yewzijian/RegTR/releases/download/v1/trained_models.zip
Dataset: https://paperswithcode.com/dataset/modelnet
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Github: https://github.com/yewzijian/regtr
Paper: https://arxiv.org/abs/2203.14517v1
Pretrained models: https://github.com/yewzijian/RegTR/releases/download/v1/trained_models.zip
Dataset: https://paperswithcode.com/dataset/modelnet
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⛓ Deep Automatic Natural Image Matting
Github: https://github.com/JizhiziLi/AIM
Paper: https://arxiv.org/abs/2107.07235
Pretrained models: https://drive.google.com/uc?export=download&id=16dd1FGMcsMTqR6EfD2T9mtRmPwxnY0zs
Dataset: https://paperswithcode.com/dataset/celebamask-hq
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Github: https://github.com/JizhiziLi/AIM
Paper: https://arxiv.org/abs/2107.07235
Pretrained models: https://drive.google.com/uc?export=download&id=16dd1FGMcsMTqR6EfD2T9mtRmPwxnY0zs
Dataset: https://paperswithcode.com/dataset/celebamask-hq
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SuperGAT
A self-supervised graph attention network (SuperGAT), an improved graph attention model for noisy graph
Code: https://github.com/dongkwan-kim/SuperGAT
Paper: https://arxiv.org/abs/2204.04879v1
Dataset: https://paperswithcode.com/dataset/ogb
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A self-supervised graph attention network (SuperGAT), an improved graph attention model for noisy graph
Code: https://github.com/dongkwan-kim/SuperGAT
Paper: https://arxiv.org/abs/2204.04879v1
Dataset: https://paperswithcode.com/dataset/ogb
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🗂 ObjectFolder 2.0: A Multisensory Object Dataset for Sim2Real Transfer
Github: https://github.com/rhgao/objectfolder
Paper: https://arxiv.org/abs/2204.02389v1
Project: https://ai.stanford.edu/~rhgao/objectfolder2.0/
Dataset: https://paperswithcode.com/dataset/objectfolder
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Github: https://github.com/rhgao/objectfolder
Paper: https://arxiv.org/abs/2204.02389v1
Project: https://ai.stanford.edu/~rhgao/objectfolder2.0/
Dataset: https://paperswithcode.com/dataset/objectfolder
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🔥 DALL·E 2
DALL·E 2 is a new AI system that can create realistic images and art from a denoscription in natural language.
Openai: https://openai.com/dall-e-2/
Paper: https://cdn.openai.com/papers/dall-e-2.pdf
Video: https://vimeo.com/692375454
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DALL·E 2 is a new AI system that can create realistic images and art from a denoscription in natural language.
Openai: https://openai.com/dall-e-2/
Paper: https://cdn.openai.com/papers/dall-e-2.pdf
Video: https://vimeo.com/692375454
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Vision Transformers for Single Image Dehazing
Code: https://github.com/IDKiro/DehazeFormer
Paper: https://arxiv.org/abs/2204.03883v1
Dataset: https://paperswithcode.com/dataset/rs-haze
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Code: https://github.com/IDKiro/DehazeFormer
Paper: https://arxiv.org/abs/2204.03883v1
Dataset: https://paperswithcode.com/dataset/rs-haze
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🔗 Unsupervised Image-to-Image Translation with Generative Prior
A novel framework GP-UNIT, to improve the overall quality and applicability of the translation algorithm
Github: https://github.com/williamyang1991/gp-unit
Paper: https://arxiv.org/abs/2204.03641v1
Datasett: https://paperswithcode.com/dataset/celeba-hq
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A novel framework GP-UNIT, to improve the overall quality and applicability of the translation algorithm
Github: https://github.com/williamyang1991/gp-unit
Paper: https://arxiv.org/abs/2204.03641v1
Datasett: https://paperswithcode.com/dataset/celeba-hq
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🔦 YOLOV5-ti-lite Object Detection Models
Code: https://github.com/texasinstruments/edgeai-yolov5
Paper: https://arxiv.org/abs/2204.06806v1
Dataset: https://paperswithcode.com/dataset/coco
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Code: https://github.com/texasinstruments/edgeai-yolov5
Paper: https://arxiv.org/abs/2204.06806v1
Dataset: https://paperswithcode.com/dataset/coco
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GitHub
GitHub - TexasInstruments/edgeai-yolov5: This repository has been deprecated. Suggest to use edgeai-mmdetection in https://git…
This repository has been deprecated. Suggest to use edgeai-mmdetection in https://github.com/TexasInstruments/edgeai-tensorlab - TexasInstruments/edgeai-yolov5
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✏️ Sat2lod2: A Software For Automated Lod-2 Modeling From Satellite-Derived Orthophoto And Digital Surface Model
The proposed method starts building detection results through a deep learning-based detector and vectorizes individual segments into polygons using a “three-step” polygon extraction method
Github: https://github.com/gdaosu/lod2buildingmodel
Paper: https://arxiv.org/abs/2204.04139v1
Datasett: https://drive.google.com/file/d/1rA7SRPbSYFJwOBc7IfXxBgmUroTOZIOF/view?usp=sharing
Video: https://youtu.be/Nn4OABsEOXk
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The proposed method starts building detection results through a deep learning-based detector and vectorizes individual segments into polygons using a “three-step” polygon extraction method
Github: https://github.com/gdaosu/lod2buildingmodel
Paper: https://arxiv.org/abs/2204.04139v1
Datasett: https://drive.google.com/file/d/1rA7SRPbSYFJwOBc7IfXxBgmUroTOZIOF/view?usp=sharing
Video: https://youtu.be/Nn4OABsEOXk
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🔎 CenterNet++ for Object Detection
Code: https://github.com/Duankaiwen/PyCenterNet
Paper: https://arxiv.org/abs/2204.08394v1
Dataset: https://paperswithcode.com/dataset/coco
Code: https://github.com/Duankaiwen/PyCenterNet
Paper: https://arxiv.org/abs/2204.08394v1
Dataset: https://paperswithcode.com/dataset/coco
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✏️ Sat2lod2: A Software For Automated Lod-2 Modeling From Satellite-Derived Orthophoto And Digital Surface Model
The proposed method starts building detection results through a deep learning-based detector and vectorizes individual segments into polygons using a “three-step” polygon extraction method
Github: https://github.com/jingkang50/openood
Paper: https://arxiv.org/abs/2204.05306v1
Dataset: https://entuedu-my.sharepoint.com/:f:/g/personal/jingkang001_e_ntu_edu_sg/Eso7IDKUKQ9AoY7hm9IU2gIBMWNnWGCYPwClpH0TASRLmg?e=iEYhXO
More tutorials: https://github.com/Jingkang50/OpenOOD/wiki/Get-Started
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The proposed method starts building detection results through a deep learning-based detector and vectorizes individual segments into polygons using a “three-step” polygon extraction method
Github: https://github.com/jingkang50/openood
Paper: https://arxiv.org/abs/2204.05306v1
Dataset: https://entuedu-my.sharepoint.com/:f:/g/personal/jingkang001_e_ntu_edu_sg/Eso7IDKUKQ9AoY7hm9IU2gIBMWNnWGCYPwClpH0TASRLmg?e=iEYhXO
More tutorials: https://github.com/Jingkang50/OpenOOD/wiki/Get-Started
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Understanding Engagement from Video Screengrabs
Code: https://github.com/wanghewei16/video-engagement-analysis
Paper: https://arxiv.org/abs/2204.06454v1
The data source: https://github.com/e-drishti/wacv2016.
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Code: https://github.com/wanghewei16/video-engagement-analysis
Paper: https://arxiv.org/abs/2204.06454v1
The data source: https://github.com/e-drishti/wacv2016.
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✔️ Localization Distillation for Dense Object Detection
Github: https://github.com/HikariTJU/LD
Paper: https://arxiv.org/abs/2102.12252
Datasett: https://paperswithcode.com/dataset/dota
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Github: https://github.com/HikariTJU/LD
Paper: https://arxiv.org/abs/2102.12252
Datasett: https://paperswithcode.com/dataset/dota
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