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Recently in AI | April 2024
High-Resolution Video Synthesis with Latent Diffusion Models
Catmull-Clark's algorithm
Face aging with Identity-preserved CGANs.
LRM : Large Reconstruction Model for Single Image to 3D
Depth Anything
Filters for edge detection
Unveiling SAM: Revolutionizing Image Segmentation with the Segment Anything Model
Data Augmentation in Classification and Segmentation: A Survey and New Strategies
Understanding DLSS: A Dive into NVIDIA's Revolutionary Technology
“Vision Transformer Adapters for Generalizable Multitask Learning”
Can AI do Math Research ?
Unmasking Skin Lesions
Skeleton project with DWPose
Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation
Diffuse, Attend, and Segment: Unsupervised Zero-Shot Segmentation using Stable Diffusion
Computed tomography scan
A step into Machine Unlearning
"MAGVIT: Masked Generative Video Transformer"
Supercharge Your Python Code with a Comprehensive Testing Strategy
Mastering Generative AI with Large Language Models
Exploring Image Similarity Search and Deduplication
Dynamical Systems & machine Learning
Reconstructing Natural Scenes from fMRI Patters Using Deep Generative Networks
“Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture”, the latest paper from Yann Lecun’s team at Meta
DeepXplore: Unleashing the Power of Automated Whitebox Testing for Deep Learning Systems
EfficientNetV2: Smaller Models & Faster Training
Depth Map
Unsupervised Learning in Spiking Neural Networks
SkinGAN Project using LaMa-Fourier
Overview of Self Supervised Learning
SAM: Segment Anything Model by Meta AI
Introduction aux Graphes Neural Networks
AI Insights
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Introduction aux Graphes Neural Networks
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SAM: Segment Anything Model by Meta AI
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Overview of Self Supervised Learning
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SkinGAN Project using LaMa-Fourier
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Unsupervised Learning in Spiking Neural Networks
AI Tasting Seminars
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Reconstructing Natural Scenes from fMRI Patters Using Deep Generative Networks
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From Dilated Convolution With Learnable Spacings to Gaussian Mixture Kernel Convolution
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A Bayesian Framework for Multivariate Multifractal Analysis of Signals and Images
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Functional Principal Component Analysis
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Training Adaptive Reconstruction Networks for Blind Inverse Problems