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adelaidepth

This repo contains the projects: 'Virtual Normal', 'DiverseDepth', and '3D Scene Shape'. They aim to solve the monocular depth estimation, 3D scene reconstruction from single image problems.

autogan

[ICCV 2019] "AutoGAN: Neural Architecture Search for Generative Adversarial Networks" by Xinyu Gong, Shiyu Chang, Yifan Jiang and Zhangyang Wang

autograd

Efficiently computes derivatives of numpy code.

chainer-gan-lib

Chainer implementation of recent GAN variants

clip-retrieval

Easily compute clip embeddings and build a clip retrieval system with them

colf

Compositional Object Light Fields code

cs281-final-project

cs281-scribe

cs281-sections

cs348k_dit

cuda-sample

CUDA official sample codes

datacomp

DataComp: In search of the next generation of multimodal datasets

droid-slam

ec2099-final-project

For ec2099 final project proposal, code by Kyle Sargent and william chang

improved_wgan_training

Code for reproducing experiments in "Improved Training of Wasserstein GANs"

ivid

PyTorch implementation of the ICCV paper "3D-aware Image Generation using 2D Diffusion Models"

kylesargent.github.io

mamba.py

A simple and efficient Mamba implementation in PyTorch and MLX.

marigold

Marigold: Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation

mintnet

MintNet: Building Invertible Neural Networks with Masked Convolutions

motionctrl

MotionCtrl: A Unified and Flexible Motion Controller for Video Generation

multinerf

A Code Release for Mip-NeRF 360, Ref-NeRF, and RawNeRF

ncsn

Noise Conditional Score Networks

nerfstudio

A collaboration friendly studio for NeRFs

objaverse-xl

🪐 Objaverse-XL is a Universe of 10M+ 3D Objects. Contains API Scripts for Downloading and Processing!

online_identification_at_scale

particle-sfm

ParticleSfM: Exploiting Dense Point Trajectories for Localizing Moving Cameras in the Wild. ECCV 2022.

perceptualsimilarity

LPIPS metric. pip install lpips

pixel-nerf

PixelNeRF Official Repository

progressive_growing_of_gans

Progressive Growing of GANs for Improved Quality, Stability, and Variation