🦾 Global Tracking Transformers

Github: https://github.com/xingyizhou/GTR

Demo: https://github.com/facebookresearch/detectron2/blob/main/GETTING_STARTED.md

Paper: https://arxiv.org/abs/2203.13250v1

Dataset: https://paperswithcode.com/dataset/mot17

https://t.iss.one/ArtificialIntelligencedl

⚡️ EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation

Github: https://github.com/tjiiv-cprg/epro-pnp

Paper: https://arxiv.org/abs/2203.13254v1

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

@ArtificialIntelligencedl

🎨 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

@ArtificialIntelligencedl

◾️ pyABC: Efficient and robust easy-to-use approximate Bayesian computation

Github: https://github.com/icb-dcm/pyabc

Paper: https://arxiv.org/abs/2203.13043v1

@ArtificialIntelligencedl

🧍 Discovering Human-Object Interaction Concepts via Self-Compositional Learning

Github: https://github.com/zhihou7/HOI-CL

Paper: https://arxiv.org/abs/2203.14272v1

Dataset: https://paperswithcode.com/dataset/hico-det

@ArtificialIntelligencedl

Semantic Line Detection Using Mirror Attention and Comparative Ranking and Matching

A novel algorithm to detect semantic lines is proposed in this paper. We develop three networks: detection network with mirror attention (D-Net) and comparative ranking and matching networks (R-Net and M-Net)

Github: https://github.com/dongkwonjin/Semantic-Line-DRM

Code: https://github.com/dongkwonjin/Semantic-Line-SLNet

Paper: https://arxiv.org/abs/2203.15285v1

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

@ArtificialIntelligencedl

Semantic Line Detection Using Mirror Attention and Comparative Ranking and Matching

A novel approach where the two processes for activity classification and entity estimation are interactive and complementary.

Github: https://github.com/jhcho99/coformer

Architecture: https://github.com/jhcho99/gsrtr

Paper: https://arxiv.org/abs/2203.16518v1

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

@ArtificialIntelligencedl

📱 Best it channels in Telegram

https://t.iss.one/ai_machinelearning_big_data - best ml channel
https://t.iss.one/ArtificialIntelligencedl - ai
https://t.iss.one/pythonl - largest python channel
https://t.iss.one/pro_python_code - python ru

https://t.iss.one/datascienceiot - ds, ml free books
https://t.iss.one/programming_books_it
https://t.iss.one/pythonlbooks - python books

https://t.iss.one/javascriptv - javascript channel
https://t.iss.one/about_javascript - advanced js
https://t.iss.one/JavaScript_testit - js tests
https://t.iss.one/Golang_google - Go channel
https://t.iss.one/golangl. -golang chat
https://t.iss.one/golang_jobsgo -golang jobs

https://t.iss.one/neural - neural nets
https://t.iss.one/hashdev - web development
https://t.iss.one/htmlcssjavas - web
https://t.iss.one/hr_itwork - jobs

https://t.iss.one/linux_kal - kali linux
https://t.iss.one/machinee_learning - ml chat
https://t.iss.one/linuxkalii - linux chat

https://t.iss.one/machinelearning_ru - ml ru
https://t.iss.one/python_testit - python tests
https://t.iss.one/csharp_ci- c#
https://t.iss.one/Machinelearningtest - machine learning test
https://t.iss.one/tensorflowblog - tensorflow
https://t.iss.one/Django_pythonl django
https://t.iss.one/javatg - java
https://t.iss.one/golangtests - Golang quizzes
https://t.iss.one/sqlhub - sql

https://t.iss.one/jsspeak - js chat

https://t.iss.one/memes_prog - it memes

💥 T5X is a modular, composable, research-friendly framework for high-performance, configurable, self-service training, evaluation, and inference of sequence models.

Github: https://github.com/google-research/t5x

Paper: https://arxiv.org/abs/2203.17189v1

@ArtificialIntelligencedl

💻 TransEditor: Transformer-Based Dual-Space GAN for Highly Controllable Facial Editing (CVPR 2022)

Recent advances like StyleGAN have promoted the growth of controllable facial editing.

Github: https://github.com/billyxyb/transeditor

Paper: https://arxiv.org/abs/2203.17266v1

@ArtificialIntelligencedl

🔍 Exploiting Explainable Metrics for Augmented SGD

A new explainability metrics that measure the redundant information in a network's layers and exploit this information to augment the Stochastic Gradient Descent

Project

Code: https://github.com/mahdihosseini/rmsgd

Paper: https://arxiv.org/pdf/2203.16723v1.pdf

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

@ArtificialIntelligencedl

🎆 Efficient Non-Autoregressive GAN Voice Conversion using VQWav2vec Features and Dynamic Convolution

Dynamic-GAN-VC (DYGAN-VC), uses a non-autoregressive structure and makes use of vector quantised embeddings obtained from a VQWav2vec model

Code: https://github.com/mingjiechen/dyganvc

Paper: https://arxiv.org/abs/2203.17172v1

Dataset: https://github.com/nii-yamagishilab/VCC2020-database

@ArtificialIntelligencedl

➕ Rethinking Portrait Matting with Privacy Preserving

Code: https://github.com/mingjiechen/dyganvc

Paper: https://arxiv.org/abs/2203.16828v1

Dataset: https://github.com/vitae-transformer/vitae-transformer-matting#ppt-setting-and-p3m-10k-dataset

@ArtificialIntelligencedl

📊 MultiMAE: Multi-modal Multi-task Masked Autoencoders

An efficient and effective pre-training strategy for Vision Transformers

Project: https://multimae.epfl.ch/

Code: https://github.com/EPFL-VILAB/MultiMAE

Paper: https://arxiv.org/abs/2204.01678

Project: https://multimae.epfl.ch/

@ArtificialIntelligencedl

📌 TESTR: Text Spotting Transformers

TExt Spotting TRansformers (TESTR), a generic end-to-end text spotting framework using Transformers for text detection and recognition in the wild

Code: https://github.com/mlpc-ucsd/testr

Paper: https://arxiv.org/abs/2204.01918

Dataset: https://ucsdcloud-my.sharepoint.com/:u:/g/personal/xiz102_ucsd_edu/EWgEM5BSRjBEua4B_qLrGR0BaombUL8K3d23ldXOb7wUNA?e=7VzH34

@ArtificialIntelligencedl

MIMDet 🎭

Unleashing Vanilla Vision Transformer with Masked Image Modeling for Object Detection

Code: https://github.com/hustvl/mimdet

Paper: https://arxiv.org/abs/2204.02964v1

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

Pretrained Model: https://dl.fbaipublicfiles.com/mae/pretrain/mae_pretrain_vit_base_full.pth

@ArtificialIntelligencedl

📐 FineDiving: A Fine-grained Dataset for Procedure-aware Action Quality Assessment

A new fine-grained dataset, called FineDiving, developed on diverse diving events with detailed annotations on action procedures

Code: https://github.com/xujinglin/finediving

Paper: https://arxiv.org/abs/2204.03646v1

Dataset: https://pan.baidu.com/s/1v85-np2FbS0J4UfAEiI4mg

@ArtificialIntelligencedl

🖋 Context-Sensitive Temporal Feature Learning for Gait Recognition

Code: https://github.com/oliverhxh/cstl

Paper: https://arxiv.org/abs/2204.03270v1


@ArtificialIntelligencedl

DaViT: Dual Attention Vision Transformer

Code: https://github.com/dingmyu/davit

Paper: https://arxiv.org/abs/2204.03645v1

Dataset: https://paperswithcode.com/dataset/ade20k

@ArtificialIntelligencedl

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

@ArtificialIntelligencedl

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

@ArtificialIntelligencedl