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

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

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

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

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

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

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

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

Pearl: Parallel Evolutionary and Reinforcement Learning Library

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

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

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

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

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

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

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

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

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

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

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

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