Data Science | Machine Learning with Python for Researchers
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The Data Science and Python channel is for researchers and advanced programmers

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Text2Video-Zero

Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators

Paper: https://arxiv.org/abs/2303.13439
Video Result: video result link
Source code: https://github.com/picsart-ai-research/text2video-zero

https://t.iss.one/DataScienceT
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Conditional Image-to-Video Generation with Latent Flow Diffusion Models

New approach for cI2V using novel latent flow diffusion models (LFDM) that synthesize an optical flow sequence in the latent space based on the given condition to warp the given image.

🖥 Github: https://github.com/nihaomiao/cvpr23_lfdm

Paper: https://arxiv.org/abs/2303.13744v1

💨 Dataset: https://drive.google.com/file/d/1dRn1wl5TUaZJiiDpIQADt1JJ0_q36MVG/view?usp=share_link

https://t.iss.one/DataScienceT
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Test of Time: Instilling Video-Language Models with a Sense of Time

GPT-5 will likely have video abilities, but will it have a sense of time? Here is answer to this question in #CVPR2023 paper by student of University of Amsterdam to learn how to instil time into video-language foundation models.

Paper:
https://arxiv.org/abs/2301.02074

Code:
https://github.com/bpiyush/TestOfTime

Project Page:
https://bpiyush.github.io/testoftime-website/

https://t.iss.one/DataScienceT
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ViperGPT: Visual Inference via Python Execution for Reasoning

ViperGPT, a framework that leverages code-generation models to compose vision-and-language models into subroutines to produce a result for any query.


Github:
https://github.com/cvlab-columbia/viper

Paper:
https://arxiv.org/pdf/2303.08128.pdf

Project:
https://paperswithcode.com/dataset/beat

https://t.iss.one/DataScienceT
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WavCaps: A ChatGPT-Assisted Weakly-Labelled Audio Captioning Dataset for Audio-Language Multimodal Research

Propose a three-stage processing pipeline for filtering noisy data and generating high-quality captions, where ChatGPT.

🖥 Github: https://github.com/xinhaomei/wavcaps

Paper: https://arxiv.org/abs/2303.17395v1

💨 Dataset: https://paperswithcode.com/dataset/sounddescs

https://t.iss.one/DataScienceT
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Human Guided Ground-truth Generation for Realistic Image Super-resolution

🖥 Github: https://github.com/chrisdud0257/hggt

Paper: https://arxiv.org/abs/2303.13069

💨 Dataset: https://paperswithcode.com/dataset/div2k

https://t.iss.one/DataScienceT
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⚡️Token Merging for Stable Diffusion

Token Merging (ToMe) speeds up transformers by merging redundant tokens, which means the transformer has to do less work.

pip install tomesd

🖥 Github: https://github.com/dbolya/tomesd

Paper: https://arxiv.org/abs/2303.17604v1

💨 Blog: https://research.facebook.com/blog/2023/2/token-merging-your-vit-but-faster/

https://t.iss.one/DataScienceT
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⭐️ HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in HuggingFace

Language serves as an interface for LLMs to connect numerous AI models for solving complicated AI tasks!

🖥 Github: https://github.com/microsoft/JARVIS

Paper: https://arxiv.org/abs/2303.17604v1

https://t.iss.one/DataScienceT
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WeakTr: Exploring Plain Vision Transformer for Weakly-supervised Semantic Segmentation

🖥 Github: https://github.com/hustvl/weaktr

Paper: https://arxiv.org/abs/2304.01184v1

💨 Dataset: https://paperswithcode.com/dataset/imagenet

https://t.iss.one/DataScienceT
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Test of Time: Instilling Video-Language Models with a Sense of Time

GPT-5 will likely have video abilities, but will it have a sense of time? Here is answer to this question in #CVPR2023 paper by student of University of Amsterdam to learn how to instil time into video-language foundation models.

Paper:
https://arxiv.org/abs/2301.02074

Code:
https://github.com/bpiyush/TestOfTime

Project Page:
https://bpiyush.github.io/testoftime-website/

https://t.iss.one/DataScienceT
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Segment Anything

The Segment Anything Model (SAM) produces high quality object masks from input prompts such as points or boxes, and it can be used to generate masks for all objects in an image.

🖥 Github: https://github.com/facebookresearch/segment-anything

⭐️ Project: https://segment-anything.com/

Paper: https://arxiv.org/abs/2304.02643v1

💨 Dataset: https://segment-anything.com/dataset/index.html

https://t.iss.one/DataScienceT
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Painter → SegGPT: Vision Foundation Models from BAAI

SegGPT, a generalist model for segmenting everything in context.

🖥 Github: https://github.com/baaivision/painter

Paper: https://arxiv.org/abs/2304.03284v1

Demo: https://huggingface.co/spaces/BAAI/SegGPT

💨 Dataset: https://paperswithcode.com/dataset/youtube-vos

https://t.iss.one/DataScienceT
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Instruction Tuning with GPT-4

First attempt to use GPT-4 to generate instruction-following data for LLM finetuning.

🖥 Github: https://github.com/Instruction-Tuning-with-GPT-4/GPT-4-LLM

Paper: https://arxiv.org/abs/2304.03277v1

Project: https://instruction-tuning-with-gpt-4.github.io/

https://t.iss.one/DataScienceT
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⚜️ OpenAGI: When LLM Meets Domain Experts

Reinforcement Learning from Task Feedback (RLTF) mechanism, which uses the task-solving result as feedback to improve the LLM's task-solving ability

git clone https://github.com/agiresearch/OpenAGI.git

🖥 Github: https://github.com/agiresearch/openagi

Paper: https://arxiv.org/pdf/2304.04370.pdf

⭐️ Dataset: https://drive.google.com/drive/folders/1AjT6y7qLIMxcmHhUBG5IE1_5SnCPR57e?usp=share_link

https://t.iss.one/DataScienceT
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⭐️ Hard Patches Mining for Masked Image Modeling

We observe that the reconstruction loss can naturally be the metric of the difficulty of the pre-training task.

🖥 Github: https://github.com/haochen-wang409/hpm

Paper: https://arxiv.org/abs/2304.05919v1

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

https://t.iss.one/DataScienceT
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