♟ Probabilistic Warp Consistency for Weakly-Supervised Semantic Correspondences
Github: https://github.com/PruneTruong/DenseMatching
Paper: https://arxiv.org/abs/2203.04279v1
Project: https://prunetruong.com/research/warpc
Dataset: https://paperswithcode.com/dataset/pf-pascal
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Github: https://github.com/PruneTruong/DenseMatching
Paper: https://arxiv.org/abs/2203.04279v1
Project: https://prunetruong.com/research/warpc
Dataset: https://paperswithcode.com/dataset/pf-pascal
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🗿 StyleNeRF: A Style-based 3D-Aware Generator for High-resolution Image Synthesis
Github: https://github.com/facebookresearch/StyleNeRF
Video: http://jiataogu.me/style_nerf
Paper: https://arxiv.org/abs/2110.08985
Project: http://jiataogu.me/style_nerf/
Dataset: https://github.com/facebookresearch/StyleNeRF#dataset
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Github: https://github.com/facebookresearch/StyleNeRF
Video: http://jiataogu.me/style_nerf
Paper: https://arxiv.org/abs/2110.08985
Project: http://jiataogu.me/style_nerf/
Dataset: https://github.com/facebookresearch/StyleNeRF#dataset
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💥 A Single Correspondence Is Enough: Robust Global Registration to Avoid Degeneracy in Urban Environments
Github: https://github.com/url-kaist/quatro
Video: http://jiataogu.me/style_nerf
Paper: https://arxiv.org/abs/2203.06612v1
Dataset: https://paperswithcode.com/dataset/kitti
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Github: https://github.com/url-kaist/quatro
Video: http://jiataogu.me/style_nerf
Paper: https://arxiv.org/abs/2203.06612v1
Dataset: https://paperswithcode.com/dataset/kitti
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🦾 Test Suites for Validating ML Models & Data
Github: https://github.com/deepchecks/deepchecks
Example: https://docs.deepchecks.com/en/stable/examples/guides/quickstart_in_5_minutes.html
Docs: https://docs.deepchecks.com/
Paper: https://arxiv.org/abs/2203.08491v1
Blog: https://deepchecks.com/blog/
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Github: https://github.com/deepchecks/deepchecks
Example: https://docs.deepchecks.com/en/stable/examples/guides/quickstart_in_5_minutes.html
Docs: https://docs.deepchecks.com/
Paper: https://arxiv.org/abs/2203.08491v1
Blog: https://deepchecks.com/blog/
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🧷 HybridNets: End2End Perception Network
Github: https://github.com/datvuthanh/HybridNets
Paper: https://arxiv.org/abs/2203.09035v1
Dataset: https://paperswithcode.com/dataset/bdd100k
Tasks: https://paperswithcode.com/task/traffic-object-detection
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Github: https://github.com/datvuthanh/HybridNets
Paper: https://arxiv.org/abs/2203.09035v1
Dataset: https://paperswithcode.com/dataset/bdd100k
Tasks: https://paperswithcode.com/task/traffic-object-detection
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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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