Superpixel-based Refinement for Object Proposal Generation

Github: https://github.com/chwilms/superpixelRefinement

Paper: https://arxiv.org/abs/2101.04574v1

👉 @bigdata_1

Contrastive Learning of Musical Representations

Github: https://github.com/spijkervet/CLMR

Paper: https://arxiv.org/abs/2103.09410

👉 @bigdata_1

Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels

Github: https://github.com/naver-ai/relabel_imagenet

Paper: https://arxiv.org/abs/2101.05022v1

👉 @bigdata_1

🔬 The Best ML Frameworks & Extensions for Scikit-learn

https://neptune.ai/blog/the-best-ml-framework-extensions-for-scikit-learn

👉 @bigdata_1

Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation

Github: https://github.com/huawei-noah/noah-research

Paper: https://arxiv.org/abs/2101.04849v1

👉 @bigdata_1

The GENRE (Generarive ENtity REtrieval) system as presented in Autoregressive Entity Retrieval implemented in pytorch.

Github: https://github.com/facebookresearch/GENRE

Paper: https://arxiv.org/abs/2103.12528v1

Dataset: https://github.com/facebookresearch/GENRE/blob/main/scripts/download_all_datasets.sh

👉 @bigdata_1

Computer Architecture-Aware Optimisation of DNA Analysis Systems

Github: https://github.com/hasindu2008/f5c

Paper: https://arxiv.org/abs/2101.05012v1

Full Documentation : https://hasindu2008.github.io/f5c/docs/overview

👉 @bigdata_1

Towards Ultra-Resolution Neural Style Transfer via Thumbnail Instance Normalization

Github: https://github.com/czczup/URST

Paper: https://arxiv.org/abs/2103.11784

Dataset: https://cocodataset.org/#download

👉 @bigdata_1

Temporal-Relational CrossTransformers for Few-Shot Action Recognition

Github: https://github.com/tobyperrett/trx

Paper: https://arxiv.org/abs/2101.06184v1

👉 @bigdata_1

🤗 ⚡️Multilingual CLIP with Huggingface + PyTorch Lightning

https://sachinruk.github.io/blog/pytorch/pytorch%20lightning/loss%20function/gpu/2021/03/07/CLIP.html#Data

CLIP: Connecting Text and Images: https://openai.com/blog/clip/


👉 @bigdata_1

Free Lunch for Few-shot Learning: Distribution Calibration

Github: https://github.com/ShuoYang-1998/ICLR2021-Oral_Distribution_Calibration

Paper: https://openreview.net/forum?id=JWOiYxMG92s

👉 @bigdata_1

Swin Transformer - PyTorch

Code: https://github.com/berniwal/swin-transformer-pytorch

Github: https://github.com/microsoft/Swin-Transformer

Paper: https://arxiv.org/abs/2103.14030v1

👉 @bigdata_1

Momentum^2 Teacher: Momentum Teacher with Momentum Statistics for Self-Supervised Learning

Github: https://github.com/zengarden/momentum2-teacher

Paper: https://arxiv.org/abs/2101.07525v1

👉 @bigdata_1

UniverseNet

UniverseNet is the state-of-the-art detector that can be trained in 24 epochs.

Github: https://github.com/shinya7y/UniverseNet

Paper: https://arxiv.org/abs/2103.14027v1

👉 @bigdata_1

TransT - Transformer Tracking

Github: https://github.com/chenxin-dlut/TransT

Paper: https://arxiv.org/abs/2103.15436

Model: https://drive.google.com/drive/folders/1GVQV1GoW-ttDJRRqaVAtLUtubtgLhWCE

👉 @bigdata_1

Animesion

DAF:RE: A CHALLENGING, CROWD-SOURCED, LARGE-SCALE, LONG-TAILED
DATASET FOR ANIME CHARACTER RECOGNITION

Code:https://github.com/arkel23/animesion

Paper: https://arxiv.org/abs/2101.08674v1

👉 @bigdata_1

Hyperbolic Graph Convolutional Auto-Encoders

Github: https://github.com/junhocho/HGCAE

Paper: https://arxiv.org/abs/2103.16046

👉 @bigdata_1

Self-Adaptive Training

Github: https://github.com/LayneH/self-adaptive-training

Paper: https://arxiv.org/abs/2101.08732v1

👉 @bigdata_1

⚡️ NeX: Real-time View Synthesis with Neural Basis Expansion

Github: https://github.com/nex-mpi/nex-code

Real-time View Synthesis with Python Code: https://analyticsindiamag.com/what-is-nex-guide-to-real-time-view-synthesis-with-python-code/

Project: https://nex-mpi.github.io/

Paper: https://arxiv.org/pdf/2103.05606.pdf

Video: https://www.youtube.com/watch?v=HyfkF7Z-ddA&ab_channel=SupasornSuwajanakorn

👉 @bigdata_1

The Ultimate Scikit-Learn Machine Learning Cheatsheet

https://www.kdnuggets.com/2021/01/ultimate-scikit-learn-machine-learning-cheatsheet.html

👉 @bigdata_1