Computer Science and Programming

2023-02-15 12:04:01 YOWOv2: A Stronger yet Efficient Multi-level Detection Framework for Real-time Spatio-temporal Action Detection

SPATIO-temporal action detection (STAD) aims to detect action instances in the current frame, which it has been widely applied, such as video surveillance and somatosensory game.

Paper:
https://arxiv.org/pdf/2302.06848.pdf

Github:
https://github.com/yjh0410/YOWOv2

Dataset:
https://drive.google.com/file/d/1Dwh90pRi7uGkH5qLRjQIFiEmMJrAog5J/view?usp=sharing

@computer_science_and_programming Open / Comment

2023-02-13 13:17:31 Gen-1: The Next Step Forward for Generative AI

Use words and images to generate new videos out of existing

Introducing Gen-1: a new AI model that uses language and images to generate new videos out of existing ones.

https://research.runwayml.com/gen1

Project:
https://research.runwayml.com/gen1

Paper:
https://arxiv.org/abs/2302.03011

Request form:
https://docs.google.com/forms/d/e/1FAIpQLSfU0O_i1dym30hEI33teAvCRQ1i8UrGgXd4BPrvBWaOnDgs9g/viewform

@computer_science_and_programming Open / Comment

2023-02-07 17:49:12 Audio AI Timeline

Here we will keep track of the latest AI models for audio generation, starting in 2023!


SingSong: Generating musical accompaniments from singing
- Paper

AudioLDM: Text-to-Audio Generation with Latent Diffusion Models
- Paper
- Code

Moûsai: Text-to-Music Generation with Long-Context Latent Diffusion
- Paper
- Code

Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Models
- Paper

Noise2Music

RAVE2
- Paper
- Code

MusicLM: Generating Music From Text
- Paper

Msanii: High Fidelity Music Synthesis on a Shoestring Budget
- Paper
- Code
- HuggingFace

ArchiSound: Audio Generation with Diffusion
- Paper
- Code

VALL-E: Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers
- Paper

@computer_science_and_programming Open / Comment

2023-01-27 10:19:21 Cut and Learn for Unsupervised Object Detection and Instance Segmentation

Cut-and-LEaRn (CutLER) is a simple approach for training object detection and instance segmentation models without human annotations. It outperforms previous SOTA by 2.7 times for AP50 and 2.6 times for AR on 11 benchmarks.

Paper:
https://arxiv.org/pdf/2301.11320.pdf

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

Demo:
https://colab.research.google.com/drive/1NgEyFHvOfuA2MZZnfNPWg1w5gSr3HOBb?usp=sharing

@computer_science_and_programming Open / Comment

2023-01-24 15:22:28 GLIGEN: Open-Set Grounded Text-to-Image Generation.

GLIGEN (Grounded-Language-to-Image Generation) a novel approach that builds upon and extends the functionality of existing pre-trained text-to-image diffusion models by enabling them to also be conditioned on grounding inputs.

Project page:
https://gligen.github.io/

Paper:
https://arxiv.org/abs/2301.07093

Github (coming soon):
https://github.com/gligen/GLIGEN

Demo:
https://huggingface.co/spaces/gligen/demo


@computer_science_and_programming Open / Comment

2023-01-19 16:22:34 Box2Mask: Box-supervised Instance Segmentation via Level-set Evolution

BoxInstSeg is a toolbox that aims to provide state-of-the-art box-supervised instance segmentation algorithms. It supports instance segmentation with only box annotations.


Github:
https://github.com/LiWentomng/BoxInstSeg

Paper:
https://arxiv.org/pdf/2212.01579.pdf

@computer_science_and_programming Open / Comment

2023-01-12 10:36:17 YOLOv8 is the newest state-of-the-art YOLO model that can be used for object detection, image classification, and instance segmentation tasks. YOLOv8 includes numerous architectural and developer experience changes and improvements over YOLOv5.

Code:
https://github.com/ultralytics/ultralytics

What's New in YOLOv8 ?
https://blog.roboflow.com/whats-new-in-yolov8/

Yolov8 Instance Segmentation (ONNX):
https://github.com/ibaiGorordo/ONNX-YOLOv8-Instance-Segmentation

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2023-01-08 18:43:25 MIT Introduction to Deep Learning - 2023 Starting soon! MIT Intro to DL is one of the most concise AI courses on the web that cover basic deep learning techniques, architectures, and applications.

2023 lectures are starting in just one day, Jan 9th!

Link to register:
http://introtodeeplearning.com

MIT Introduction to Deep Learning The 2022 lectures can be found here:

https://m.youtube.com/playlist?list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI

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2023-01-06 15:01:18 PACO: Parts and Attributes of Common Objects

Sometimes object detection is not enough and you need more detail about object. Especially, when parts of objects is matters in your task. Then this dataset is for you from Facebook research team.

PACO is a detection dataset that goes beyond traditional object boxes and masks and provides richer annotations such as part masks and attributes. It spans 75 object categories, 456 object-part categories and 55 attributes across image (LVIS) and video (Ego4D) datasets.

Paper:
https://arxiv.org/pdf/2301.01795.pdf

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

Visualization:
https://github.com/facebookresearch/paco/tree/main/notebooks

@computer_science_and_programming Open / Comment

2022-08-15 07:53:40 Harvard CS109A #DataScience course materials — huge collection free & open!

1. Lecture notes
2. R code, #Python notebooks
3. Lab material
4. Advanced sections
and more ...

https://harvard-iacs.github.io/2019-CS109A/pages/materials.html

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