Papers with Code 2021 : A Year in Review
https://www.kdnuggets.com/2021/12/2021-year-review-amazing-ai-papers.html
https://medium.com/paperswithcode/papers-with-code-2021-a-year-in-review-de75d5a77b8b
👉 @bigdata_1
https://www.kdnuggets.com/2021/12/2021-year-review-amazing-ai-papers.html
https://medium.com/paperswithcode/papers-with-code-2021-a-year-in-review-de75d5a77b8b
👉 @bigdata_1
PyramidTNT: Improved Transformer-in-Transformer Baselines with Pyramid Architecture
PyramidTNT achieves better performances than the previous state-of-the-art vision transformers such as Swin Transformer
Github: https://github.com/huawei-noah/CV-backbones
Paper: https://arxiv.org/abs/2201.00978v1
GhostNet: https://github.com/huawei-noah/CV-backbones/tree/master/ghostnet_pytorch
👉 @bigdata_1
PyramidTNT achieves better performances than the previous state-of-the-art vision transformers such as Swin Transformer
Github: https://github.com/huawei-noah/CV-backbones
Paper: https://arxiv.org/abs/2201.00978v1
GhostNet: https://github.com/huawei-noah/CV-backbones/tree/master/ghostnet_pytorch
👉 @bigdata_1
AV-HuBERT (Audio-Visual Hidden Unit BERT)
AV-HuBERT is a self-supervised representation learning framework for audio-visual speech.
Github: https://github.com/facebookresearch/av_hubert
Facebook AI: https://ai.facebook.com/blog/ai-that-understands-speech-by-looking-as-well-as-hearing/
Paper: https://arxiv.org/abs/2201.02184
👉 @bigdata_1
AV-HuBERT is a self-supervised representation learning framework for audio-visual speech.
Github: https://github.com/facebookresearch/av_hubert
Facebook AI: https://ai.facebook.com/blog/ai-that-understands-speech-by-looking-as-well-as-hearing/
Paper: https://arxiv.org/abs/2201.02184
👉 @bigdata_1
GitHub
GitHub - facebookresearch/av_hubert: A self-supervised learning framework for audio-visual speech
A self-supervised learning framework for audio-visual speech - facebookresearch/av_hubert
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pymdp: A Python library for active inference in discrete state spaces
Github: https://github.com/infer-actively/pymdp
Paper: https://arxiv.org/abs/2201.03904v1
Docs: https://pymdp-rtd.readthedocs.io/
Tasks: https://paperswithcode.com/task/bayesian-inference
👉 @bigdata_1
Github: https://github.com/infer-actively/pymdp
Paper: https://arxiv.org/abs/2201.03904v1
Docs: https://pymdp-rtd.readthedocs.io/
Tasks: https://paperswithcode.com/task/bayesian-inference
👉 @bigdata_1
Uniformer: Unified Transformer for Efficient Spatiotemporal Representation Learning
Github: https://github.com/sense-x/uniformer
Paper: https://arxiv.org/abs/2201.04676v1
Tasks: https://paperswithcode.com/dataset/kinetics-600
👉 @bigdata_1
Github: https://github.com/sense-x/uniformer
Paper: https://arxiv.org/abs/2201.04676v1
Tasks: https://paperswithcode.com/dataset/kinetics-600
👉 @bigdata_1
Introducing StylEx: A New Approach for Visual Explanation of Classifiers
Github: https://explaining-in-style.github.io/
Code: https://github.com/google/explaining-in-style
Article: https://ai.googleblog.com/2022/01/introducing-stylex-new-approach-for.html
Video: https://explaining-in-style.github.io/#video
👉 @bigdata_1
Github: https://explaining-in-style.github.io/
Code: https://github.com/google/explaining-in-style
Article: https://ai.googleblog.com/2022/01/introducing-stylex-new-approach-for.html
Video: https://explaining-in-style.github.io/#video
👉 @bigdata_1
Omnivore: A Single Model for Many Visual Modalities
Github: https://github.com/facebookresearch/omnivore
Code: https://github.com/facebookresearch/omnivore/blob/main/inference_tutorial.ipynb
Paper: https://arxiv.org/abs/2201.08377
Dataset: https://paperswithcode.com/dataset/epic-kitchens-100
👉 @bigdata_1
Github: https://github.com/facebookresearch/omnivore
Code: https://github.com/facebookresearch/omnivore/blob/main/inference_tutorial.ipynb
Paper: https://arxiv.org/abs/2201.08377
Dataset: https://paperswithcode.com/dataset/epic-kitchens-100
👉 @bigdata_1
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The first high-performance self-supervised algorithm that works for speech, vision, and text
Github: https://github.com/pytorch/fairseq/tree/main/examples/data2vec
Paper: https://ai.facebook.com/research/data2vec-a-general-framework-for-self-supervised-learning-in-speech-vision-and-language
Meta AI: https://ai.facebook.com/blog/the-first-high-performance-self-supervised-algorithm-that-works-for-speech-vision-and-text/
👉 @bigdata_1
Github: https://github.com/pytorch/fairseq/tree/main/examples/data2vec
Paper: https://ai.facebook.com/research/data2vec-a-general-framework-for-self-supervised-learning-in-speech-vision-and-language
Meta AI: https://ai.facebook.com/blog/the-first-high-performance-self-supervised-algorithm-that-works-for-speech-vision-and-text/
👉 @bigdata_1
ConvMixer, an extremely simple model that is similar in spirit to the ViT and the even-more-basic MLP-Mixer
Github: https://github.com/locuslab/convmixer
Paper: https://arxiv.org/pdf/2201.09792v1.pdf
👉 @bigdata_1
Github: https://github.com/locuslab/convmixer
Paper: https://arxiv.org/pdf/2201.09792v1.pdf
👉 @bigdata_1
Pearl: Parallel Evolutionary and Reinforcement Learning Library
Github: https://github.com/locuslab/convmixer
Paper: https://arxiv.org/pdf/2201.09568v1.pdf
👉 @bigdata_1
Github: https://github.com/locuslab/convmixer
Paper: https://arxiv.org/pdf/2201.09568v1.pdf
👉 @bigdata_1
When Shift Operation Meets Vision Transformer: An Extremely Simple Alternative to Attention Mechanism
Github: https://github.com/microsoft/SPACH
Paper: https://arxiv.org/abs/2201.10801v1
Dataset: https://paperswithcode.com/dataset/coco
👉 @bigdata_1
Github: https://github.com/microsoft/SPACH
Paper: https://arxiv.org/abs/2201.10801v1
Dataset: https://paperswithcode.com/dataset/coco
👉 @bigdata_1
PortaSpeech: Portable and High-Quality Generative Text-to-Speech
Github: https://github.com/keonlee9420/PortaSpeech
Paper: https://arxiv.org/pdf/2109.15166v4.pdf
Dataset: https://paperswithcode.com/dataset/ljspeech
👉 @bigdata_1
Github: https://github.com/keonlee9420/PortaSpeech
Paper: https://arxiv.org/pdf/2109.15166v4.pdf
Dataset: https://paperswithcode.com/dataset/ljspeech
👉 @bigdata_1
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VRT: A Video Restoration Transformer
Github: https://github.com/jingyunliang/vrt
Paper: https://arxiv.org/abs/2201.12288
Dataset: https://paperswithcode.com/dataset/gopro
👉 @bigdata_1
Github: https://github.com/jingyunliang/vrt
Paper: https://arxiv.org/abs/2201.12288
Dataset: https://paperswithcode.com/dataset/gopro
👉 @bigdata_1
Competition-Level Code Generation with AlphaCode
Github: https://github.com/deepmind/code_contests
Paper: https://storage.googleapis.com/deepmind-media/AlphaCode/competition_level_code_generation_with_alphacode.pdf
Dataset: https://paperswithcode.com/dataset/humaneval
👉 @bigdata_1
Github: https://github.com/deepmind/code_contests
Paper: https://storage.googleapis.com/deepmind-media/AlphaCode/competition_level_code_generation_with_alphacode.pdf
Dataset: https://paperswithcode.com/dataset/humaneval
👉 @bigdata_1
VOS: Learning What You Don't Know by Virtual Outlier Synthesis
Github: https://github.com/deeplearning-wisc/vos
Paper: https://arxiv.org/pdf/2202.01197v2.pdf
Dataset: https://paperswithcode.com/dataset/bdd100k
👉 @bigdata_1
Github: https://github.com/deeplearning-wisc/vos
Paper: https://arxiv.org/pdf/2202.01197v2.pdf
Dataset: https://paperswithcode.com/dataset/bdd100k
👉 @bigdata_1
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The easiest way to the neuroscience world with the shield for RaspberryPi
Github: https://github.com/Ildaron/EEGwithRaspberryPI
Paper: https://arxiv.org/pdf/2202.01936v1.pdf
Project: https://www.crowdsupply.com/hackerbci/pieeg
👉 @bigdata_1
Github: https://github.com/Ildaron/EEGwithRaspberryPI
Paper: https://arxiv.org/pdf/2202.01936v1.pdf
Project: https://www.crowdsupply.com/hackerbci/pieeg
👉 @bigdata_1
Two-Dimensional Tensors in Pytorch
https://machinelearningmastery.com/two-dimensional-tensors-in-pytorch/
One-Dimensional Tensors: https://machinelearningmastery.com/one-dimensional-tensors-in-pytorch/
PyTorch tensor Tutorial: https://pytorch.org/tutorials/beginner/basics/tensorqs_tutorial.html
👉 @bigdata_1
https://machinelearningmastery.com/two-dimensional-tensors-in-pytorch/
One-Dimensional Tensors: https://machinelearningmastery.com/one-dimensional-tensors-in-pytorch/
PyTorch tensor Tutorial: https://pytorch.org/tutorials/beginner/basics/tensorqs_tutorial.html
👉 @bigdata_1
DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generative Transformers
Github: https://github.com/j-min/dalleval
Paper: https://arxiv.org/pdf/2202.01936v1.pdf
Data: https://drive.google.com/drive/folders/1Bza2zyvHLvComohZ9PAGyykY7sm7JoIH
Dataset: https://paperswithcode.com/dataset/conceptual-captions
👉 @bigdata_1
Github: https://github.com/j-min/dalleval
Paper: https://arxiv.org/pdf/2202.01936v1.pdf
Data: https://drive.google.com/drive/folders/1Bza2zyvHLvComohZ9PAGyykY7sm7JoIH
Dataset: https://paperswithcode.com/dataset/conceptual-captions
👉 @bigdata_1
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FILM: Frame Interpolation for Large Scene Motion
Github: https://github.com/google-research/frame-interpolation
Paper: https://arxiv.org/pdf/2202.04901.pdf
Video: https://www.youtube.com/watch?v=OAD-BieIjH4
Project: https://film-net.github.io/
👉 @bigdata_1
Github: https://github.com/google-research/frame-interpolation
Paper: https://arxiv.org/pdf/2202.04901.pdf
Video: https://www.youtube.com/watch?v=OAD-BieIjH4
Project: https://film-net.github.io/
👉 @bigdata_1
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HOW TO TELL IF YOU HAVE TRAINED YOUR MODEL WITH ENOUGH DATA ?
https://calculatedcontent.com/2021/07/09/how-to-tell-if-you-have-trained-your-model-with-enough-data/
👉 @bigdata_1
https://calculatedcontent.com/2021/07/09/how-to-tell-if-you-have-trained-your-model-with-enough-data/
👉 @bigdata_1
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A lightweight vision library for performing large scale object detection & instance segmentation
Github: https://github.com/obss/sahi
Paper: https://arxiv.org/abs/2202.06934v1
Kaggle notebook: https://www.kaggle.com/remekkinas/sahi-slicing-aided-hyper-inference-yv5-and-yx
Dataset: https://paperswithcode.com/dataset/xview
👉 @bigdata_1
Github: https://github.com/obss/sahi
Paper: https://arxiv.org/abs/2202.06934v1
Kaggle notebook: https://www.kaggle.com/remekkinas/sahi-slicing-aided-hyper-inference-yv5-and-yx
Dataset: https://paperswithcode.com/dataset/xview
👉 @bigdata_1
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