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MULTIMODAL AI

Segment Anything Meets Point Tracking: SAM-PT Model

By

@_akhaliq

–

04 July 2023 6h55

Segment Anything Meets Point Tracking

paper page: https://t.co/NCXpZz6ifd

The Segment Anything Model (SAM) has established itself as a powerful zero-shot image segmentation model, employing interactive prompts such as points to generate masks. This paper presents SAM-PT, a… pic.twitter.com/1kKzl3FnUM
— AK (@_akhaliq) 4 juillet 2023

Segment Anything Meets Point Tracking paper page: https://
huggingface.co/papers/2307.01
197
… The Segment Anything Model (SAM) has established itself as a powerful zero-shot image segmentation model, employing interactive prompts such as points to generate masks. This paper presents SAM-PT, a

→ View original post on X — @_akhaliq

4 July 2023
SketchMetaFace: Learning-based Interface for 3D Character Face Modeling

By

@_akhaliq

–

04 July 2023 6h49

SketchMetaFace: A Learning-based Sketching Interface for High-fidelity 3D Character Face Modeling

paper page: https://t.co/kh6gTS5yWR

Modeling 3D avatars benefits various application scenarios such as AR/VR, gaming, and filming. Character faces contribute significant diversity… pic.twitter.com/b322anqpmC
— AK (@_akhaliq) 4 juillet 2023

SketchMetaFace: A Learning-based Sketching Interface for High-fidelity 3D Character Face Modeling paper page: https://
huggingface.co/papers/2307.00
804
… Modeling 3D avatars benefits various application scenarios such as AR/VR, gaming, and filming. Character faces contribute significant diversity

→ View original post on X — @_akhaliq

4 July 2023
DisCo: Disentangled Control for Human Dance Generation

By

@_akhaliq

–

04 July 2023 6h24

DisCo: Disentangled Control for Referring Human Dance Generation in Real World

paper page: https://t.co/bL1fWJCLcs

Generative AI has made significant strides in computer vision, particularly in image/video synthesis conditioned on text descriptions. Despite the advancements, it… pic.twitter.com/qmZYkzyx4U
— AK (@_akhaliq) 4 juillet 2023

DisCo: Disentangled Control for Referring Human Dance Generation in Real World paper page: https://
huggingface.co/papers/2307.00
040
… Generative AI has made significant strides in computer vision, particularly in image/video synthesis conditioned on text descriptions. Despite the advancements, it

→ View original post on X — @_akhaliq

4 July 2023
MVDiffusion: Multi-view Image Generation with Correspondence-Aware Diffusion

By

@_akhaliq

–

04 July 2023 5h28

MVDiffusion: Enabling Holistic Multi-view Image Generation with Correspondence-Aware Diffusion

paper page: https://t.co/QXHUkIC7x2

paper introduces MVDiffusion, a simple yet effective multi-view image generation method for scenarios where pixel-to-pixel correspondences are… pic.twitter.com/zzqvc7f7aB
— AK (@_akhaliq) 4 juillet 2023

MVDiffusion: Enabling Holistic Multi-view Image Generation with Correspondence-Aware Diffusion paper page: https://
huggingface.co/papers/2307.01
097
… paper introduces MVDiffusion, a simple yet effective multi-view image generation method for scenarios where pixel-to-pixel correspondences are

→ View original post on X — @_akhaliq

4 July 2023
Vision Transformers: Tokenizing Images Like Language Models

By

@rasbt

–

03 July 2023 17h40

In a tweet: similar to LLMs (language transformers) but tokenizing images instead of text:

→ View original post on X — @rasbt

3 July 2023
Vision Transformers for Images and LLMs for Text

By

@rasbt

–

03 July 2023 17h13

Oh this post is about vision transformers for images and LLMs for text

→ View original post on X — @rasbt

3 July 2023
Reducing GPU Memory for LLMs and Vision Transformers in PyTorch

By

@rasbt

–

03 July 2023 17h08

One of the big bottlenecks with LLMs & Vision Transformers is GPU memory on consumer devices. Wrote about my favorite techniques for reducing peak memory in PyTorch: https://
lightning.ai/pages/communit
y/tutorial/pytorch-memory-vit-llm/
… Focused on techniques that don't require architecture changes! Suggestions welcome!

→ View original post on X — @rasbt

3 July 2023
SAM: Revolutionary Image Segmentation Model with Unmatched Precision

By

@learnopencv

–

03 July 2023 16h01

🎥New Video:https://t.co/MfidGJzK7w

Dive into the specifics of SAM in our latest video – a game-changing image segmentation model with unmatched precision. #AI #ImageSegmentation #AIInnovation #computervision pic.twitter.com/PBvhLh5BjL
— Satya Mallick (@LearnOpenCV) 3 juillet 2023

New Video: https://
youtube.com/watch?v=mtHEBU
dYRYU
… Dive into the specifics of SAM in our latest video – a game-changing image segmentation model with unmatched precision. #AI #ImageSegmentation #AIInnovation #computervision

→ View original post on X — @learnopencv

3 July 2023
Clarifying terminology: LMs, LLMs, and MLLMs explained

By

@jeande_d

–

03 July 2023 15h55

The terms are confusing, I know. LMs are language models. LLMs are large LMs. MLLMs are multimodal LLMs where LLMs are treated as the "prime generalization engine". People using MLLMs in papers should probably say LMM(large multimodals) but I guess they append LLMs to take

→ View original post on X — @jeande_d

3 July 2023
AI Amplifies Human Biases: Challenge Algorithmic Outcomes

By

@pascal_bornet

–

03 July 2023 7h55

This is how #AI amplifies our human #biases!

Just 3% images of 'judges photos' were women vs. reality's 34%. It depicted 'fast-food workers' as 70% darker skin, while 70% are white in reality

A key skill of the future is to know how to challenge AI outcomes!

Ct: @Leonardonclt pic.twitter.com/qDTmSPiGxc
— Pascal Bornet (@pascal_bornet) 3 juillet 2023

This is how #AI amplifies our human #biases! Just 3% images of 'judges photos' were women vs. reality's 34%. It depicted 'fast-food workers' as 70% darker skin, while 70% are white in reality A key skill of the future is to know how to challenge AI outcomes! Ct: @Leonardonclt

→ View original post on X — @pascal_bornet

3 July 2023

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