🔥Model Inversion Attack ToolBox v2.0🔥

🖥 Github: https://github.com/ffhibnese/model-inversion-attack-toolbox

📕 Paper: https://arxiv.org/abs/2410.05159v1

🤗 Dataset: https://paperswithcode.com/dataset/ffhq

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SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree

🖥 Github: https://github.com/mark12ding/sam2long

📕 Paper: https://arxiv.org/abs/2410.16268v1

🤗 HF: https://huggingface.co/papers/2410.16268

Don’t sleep on Vision Language Models (VLMs).

With the releases of Llama 3.2 and ColQwen2, multimodal models are gaining more and more traction.

VLMs are multimodal models that can handle image and text modalities:

Input: Image and text
Output: Text

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• image encoder (e.g., CLIP, SigLIP)
• embedding projector to align image and text representations
• text decoder (e.g., Vicuna, Gemma)

huggingface.co/blog/vlms

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Constrained Diffusion Implicit Models!

We use diffusion models to solve noisy inverse problems like inpainting, sparse-recovery, and colorization. 10-50x faster than previous methods!

Paper: arxiv.org/pdf/2411.00359

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