✏️ Deep Geometrized Cartoon Line Inbetweening

Method can effectively capture the sparsity and unique structure of line drawings while preserving the details during inbetweening.

🖥 Github: https://github.com/lisiyao21/animeinbet

☑️ Demo: https://youtu.be/iUF-LsqFKpI?si=9FViAZUyFdSfZzS5

📕 Paper: https://arxiv.org/pdf/2309.16643v1.pdf

⭐️ Dataset: https://drive.google.com/file/d/1SNRGajIECxNwRp6ZJ0IlY7AEl2mRm2DR/view?usp=sharing

@Machine_learn

Book: Generative Deep Learning
Teaching Machines to Paint, Write, Compose, and Play
Authors: David Foster
ISBN: 978-1-098-13418-1
year: 2023
pages: 456
Tags:#GAN
@Machine_learn

Class Incremental Learning via Likelihood Ratio Based Task Prediction

🖥 Github: https://github.com/linhaowei1/tplr

📕 Paper: https://arxiv.org/pdf/2309.15048v1.pdf

🔥 Dataset: https://paperswithcode.com/dataset/cifar-10

@Machine_learn

Atom2D

🖥 Github: https://github.com/vincentx15/atom2d

📕 Paper: https://arxiv.org/pdf/2309.16519v1.pdf

🔥 Dataset: https://paperswithcode.com/dataset/atom3d

@Machine_learn

☑️ Efficient Streaming Language Models with Attention Sinks

StreamingLLM, an efficient framework that enables LLMs trained with a finite length attention window to generalize to infinite sequence length without any fine-tuning.

🖥 Github: https://github.com/mit-han-lab/streaming-llm

📕 Paper: http://arxiv.org/abs/2309.17453

⭐️ Dataset: https://paperswithcode.com/dataset/pg-19

@Machine_learn

🤖 GenSim: Generating Robotic Simulation Tasks via Large Language Models


🖥 Github: https://github.com/liruiw/gensim

✔️ Project: https://liruiw.github.io/gensim

📕 Paper: https://arxiv.org/abs/2310.01361v1

✅ Dataset: https://huggingface.co/datasets/Gen-Sim/Gen-Sim

⭐️ Demos: https://huggingface.co/spaces/Gen-Sim/Gen-Sim

@Machine_learn

✅️ T3Bench: Benchmarking Current Progress in Text-to-3D Generation



🖥 Github: https://github.com/THU-LYJ-Lab/T3Bench

📕 Paper: https://arxiv.org/abs/2310.02977v1

⭐️ Dataset: https://paperswithcode.com/dataset/nerf

@Machine_learn

💻 Graph Structure Learning Benchmark (GSLB)


pip install GSLB

🖥 Github: https://github.com/gsl-benchmark/gslb

📕 Paper: https://arxiv.org/abs/2310.05163v1

⭐️ Paper collection: https://github.com/GSL-Benchmark/Awesome-Graph-Structure-Learning

@Machine_learn

G4SATBench

🖥 Github: https://github.com/zhaoyu-li/g4satbench

📕 Paper: https://arxiv.org/pdf/2309.16941v1.pdf

🔥 Tasks: https://paperswithcode.com/task/benchmarking

@Machine_learn

Book: ArtificialIntelligence Programming
withPython F R O MZ E R OT OH E R O
Authors: Perry Xiao
ISBN: 978-1-119-82094-9 (ebk)
year: 2022
pages: 716
Tags:#AI #DL
@Machine_learn

Code for MIMO Activation Function

🖥 Github: https://github.com/ljy9912/mimo_nn

📕 Paper: https://arxiv.org/pdf/2309.17194v1.pdf

🔥 Datasets: https://paperswithcode.com/dataset/cifar-10

@Machine_learn

🌽 Harnessing Administrative Data Inventories to Create a Reliable Transnational Reference Database for Crop Type Monitoring


🖥 Github: https://github.com/maja601/eurocrops

📕 Paper: https://arxiv.org/pdf/2310.06393v1.pdf

⭐️ Dataset: https://syncandshare.lrz.de/getlink/fiAD95cTrXbnKMrdZYrFFcN8/

@Machine_learn

✅ Mini-DALLE3: Interactive Text to Image by Prompting Large Language Models


🖥 Github: https://github.com/Zeqiang-Lai/Mini-DALLE3

📕 Paper: https://arxiv.org/abs/2310.07653v1

⭐️ Dataset: https://paperswithcode.com/dataset/mmlu

@Machine_learn

AG3D: Learning to Generate 3D Avatars from 2D Image Collections (ICCV 2023)



🖥 Github: https://github.com/zj-dong/AG3D

📕 Paper: https://arxiv.org/abs/2305.02312

🚀Video: https://youtu.be/niP1YhJXEBE

⭐️ Project: https://zj-dong.github.io/AG3D/

@Machine_learn

Book: Python for Scientists
Third Edition
Authors: JOHN M. STEWART
ISBN: 978-1-119-82094-9 (ebk)
year: 2023
pages: 301
Tags:#Python
@Machine_learn

STGM: Spatio-Temporal Graph Mixformer for Traffic Forecasting

🖥 Github: https://github.com/Mouradost/STGM

📕 Paper: https://www.sciencedirect.com/science/article/abs/pii/S0957417423007832?via%3Dihub

🔥 Datasets: https://paperswithcode.com/dataset/metr-la

↪️ Tasks: https://paperswithcode.com/task/traffic-prediction

@Machine_learn

PHA

cd PHA
pip install -r requirements.txt

🖥 Github: https://github.com/bumble666/pha

📕 Paper: https://arxiv.org/pdf/2310.11670v1.pdf

🔥 Datasets: https://paperswithcode.com/dataset/glue

@Machine_learn

Putting the Object Back into Video Object Segmentation (Cutie)


git clone https://github.com/hkchengrex/Cutie.git

🖥 Github: https://github.com/hkchengrex/Cutie

🖥 Colab: https://colab.research.google.com/drive/1yo43XTbjxuWA7XgCUO9qxAi7wBI6HzvP?usp=sharing

📕 Paper: https://arxiv.org/abs/2310.12982v1

🚀Project: https://hkchengrex.github.io/Cutie/

@Machine_learn

🏅MixSort

MixSort is the proposed baseline tracker in SportMOT.

🖥 Github: https://github.com/MCG-NJU/MixSort

📕 Paper: https://arxiv.org/pdf/2304.05170.pdf

⭐️ SportsMOT: https://github.com/MCG-NJU/SportsMOT

@Machine_learn