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A latent text-to-image diffusion model
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.
Google Research
This repository contains implementations and illustrative code to accompany DeepMind publications
Code release for NeRF (Neural Radiance Fields)
A unified framework for 3D content generation.
A simplified implemention of Faster R-CNN that replicate performance from origin paper
HuggingLLM, Hugging Future.
Code for "LoFTR: Detector-Free Local Feature Matching with Transformers", CVPR 2021, T-PAMI 2022
NeRF (Neural Radiance Fields) and NeRF in the Wild using pytorch-lightning
A Modular Framework for 3D Gaussian Splatting and Beyond
[ECCV`24&ICLR`25] CityGaussian Series for High-quality Large-Scale Scene Reconstruction with Gaussians
[ECCV'2024] Gaussian Grouping for open-world Anything reconstruction, segmentation and editing.
3D mesh stylization driven by a text input in PyTorch
The official implementation of Segment Any 3D GAussians (AAAI-25)
SynCity: Training-Free Generation of 3D Worlds
Joint Deep Matcher for Points and Lines 🖼️💥🖼️ (ICCV 2023)
Implementation of the paper "DeepLSD: Line Segment Detection and Refinement with Deep Image Gradients"
This is a toolbox repository to help evaluate various methods that perform image matching from a pair of images.
Joint deep network for feature line detection and description
Public release of the Image Matching Benchmark: https://image-matching-challenge.github.io
[3DV 2026] "SceneGen: Single-Image 3D Scene Generation in One Feedforward Pass"
Training code for "Radiance Meshes for Volumetric Reconstruction".
(CVPR 2025 Highlight) The Scene Language: Representing Scenes with Programs, Words, and Embeddings
A curried list of recent literature of 3D Gaussians
CVPR2024 | LASA: Instance Reconstruction from Real Scans using A Large-scale Aligned Shape Annotation Dataset
The Progressive-X algorithm proposed in paper: Daniel Barath and Jiri Matas; Progressive-X: Efficient, Anytime, Multi-Model Fitting Algorithm, International Conference on Computer Vision, 2019. It …