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This is the source code to Jon Barron's public academic website: https://jonbarron.info/. You are welcome to clone this code for your own personal use, just please attribute the source to the original website or to this repo. If you do clone this website, feel free to add an attribution link to your own downstream website in index.html if you want.

Sam Motamed's Projects

big_vision icon big_vision

Official codebase used to develop Vision Transformer, SigLIP, MLP-Mixer, LiT and more.

custom-diffusion icon custom-diffusion

Custom Diffusion: Multi-Concept Customization of Text-to-Image Diffusion (CVPR 2023)

diffusers icon diffusers

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch

elite icon elite

Official Implementation of "ELITE: Encoding Visual Concepts into Textual Embeddings for Customized Text-to-Image Generation"

generative-visual-prompt icon generative-visual-prompt

Code for the NeurIPS 2022 paper "Generative Visual Prompt: Unifying Distributional Control of Pre-Trained Generative Models"

ict icon ict

High-Fidelity Pluralistic Image Completion with Transformers (ICCV 2021)

latent-nerf icon latent-nerf

Official Implementation for "Latent-NeRF for Shape-Guided Generation of 3D Shapes and Textures"

mymat icon mymat

MAT: Mask-Aware Transformer for Large Hole Image Inpainting

nerf-pytorch icon nerf-pytorch

A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.

photosketch icon photosketch

Code for Photo-Sketching: Inferring Contour Drawings from Images :dog:

segment-anything icon segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

tcav icon tcav

Code for the TCAV ML interpretability project

text2video-zero icon text2video-zero

[ICCV 2023 Oral] Text-to-Image Diffusion Models are Zero-Shot Video Generators

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