OSSO: Obtaining Skeletal Shape from Outside (CVPR 2022)

Given a body shape with SMPL or STAR topology (in blue), we infer the underlying skeleton (in yellow).

Code: https://arxiv.org/abs/2204.10129v1

Paper: https://arxiv.org/abs/2204.09838v1

Dataset: https://paperswithcode.com/dataset/agora

👉 @bigdata_1

YOLOP: You Only Look Once for Panoptic Driving Perception

Github: https://github.com/hustvl/yolop

Paper: https://arxiv.org/abs/2108.11250v2

👉 @bigdata_1

Glass Segmentation with RGB-Thermal Image Pairs

Github: https://github.com/dong-huo/rgb-t-glass-segmentation

Paper: https://arxiv.org/abs/2204.05453v2

Datasett: https://drive.google.com/file/d/1ysG04qGmnZv7UaybZUuyybaJYJLUkNHX/view?usp=sharing

👉 @bigdata_1

Understanding and Accelerating Neural Architecture Search with Training-Free and Theory-Grounded Metrics

Github: https://github.com/vita-group/tegnas

Paper: https://arxiv.org/abs/2108.11939v1

👉 @bigdata_1

Parametric Distributionally Robust Optimization

Github: https://github.com/pmichel31415/P-DRO

Paper: https://arxiv.org/abs/2204.06340v1

Datasett: https://paperswithcode.com/dataset/celeba

👉 @bigdata_1

11 Best Data Science Education Platforms

https://www.kdnuggets.com/2021/08/11-best-data-science-education-platforms.html

👉 @bigdata_1

Deep-significance: Easy and Better Significance Testing for Deep Neural Networks

Github: https://github.com/Kaleidophon/deep-significance

Paper: https://arxiv.org/abs/2204.06815v1

Examples: https://github.com/Kaleidophon/deep-significance#examples

👉 @bigdata_1

Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation

Github: https://github.com/ofirpress/attention_with_linear_biases

Paper: https://ofir.io/train_short_test_long.pdf

Fairseq: https://github.com/pytorch/fairseq

👉 @bigdata_1

An Extendable, Efficient and Effective Transformer-based Object Detector

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

Paper: https://arxiv.org/abs/2204.07962v1

Dataset: https://paperswithcode.com/dataset/coco

👉 @bigdata_1

A Partition Filter Network for Joint Entity and Relation Extraction

Github: https://github.com/Coopercoppers/PFN

Paper: https://arxiv.org/abs/2108.12202v2

👉 @bigdata_1

DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings


Code: https://github.com/voidism/diffcse

Paper: https://arxiv.org/abs/2204.10298v1

Dataset: https://paperswithcode.com/dataset/sst

👉 @bigdata_1

Iterative Filter Adaptive Network for Single Image Defocus Deblurring

Github: https://github.com/codeslake/IFAN

Paper: https://arxiv.org/abs/2108.13610v1

👉 @bigdata_1

NAFSSR: Stereo Image Super-Resolution Using NAFNet

Github: https://github.com/megvii-research/NAFNet

Paper: https://arxiv.org/abs/2204.08714v1

Dataset: https://paperswithcode.com/dataset/kitti

Demo: https://colab.research.google.com/drive/1dkO5AyktmBoWwxBwoKFUurIDn0m4qDXT?usp=sharing

👉 @bigdata_1

Anomaly detection using zscore and modified zscore

https://www.kaggle.com/code/jainyk/anomaly-detection-using-zscore-and-modified-zscore/notebook

👉 @bigdata_1

PyGCL: Graph Contrastive Learning for PyTorch

Github: https://github.com/GraphCL/PyGCL

Paper: https://arxiv.org/abs/2109.01116v1

👉 @bigdata_1

Generalising via Meta-Examples for Continual Learning in the Wild

Github: https://github.com/alessiabertugli/FUSION

Article: https://arxiv.org/abs/2101.12081v1

👉 @bigdata_1

SOLD² - Self-supervised Occlusion-aware Line Description and Detection

Github: https://github.com/cvg/SOLD2

Paper: https://arxiv.org/abs/2104.03362

👉 @bigdata_1

MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment

Github: https://github.com/iigroup/maniqa

Paper: https://arxiv.org/abs/2204.08958v1

Dataset: https://paperswithcode.com/dataset/kitti

Demo: https://paperswithcode.com/dataset/pipal-perceptual-iqa-dataset

👉 @bigdata_1

NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo

Github: https://github.com/weiyithu/nerfingmvs

Paper: https://arxiv.org/abs/2109.01129v1

Project: https://weiyithu.github.io/NerfingMVS

👉 @bigdata_1

Simulating Fluids in Real-World Still Images

surface-based layered representation(SLR), which decomposes the fluid and the static objects in the scene, to better synthesize the animated videos from a single fluid imagе

Code: https://github.com/generalizable-neural-performer/gnr

Paper: http://arxiv.org/abs/2204.11335

Project: https://simulatingfluids.github.io/

👉 @bigdata_1