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DoF-NeRF: Depth-of-Field Meets Neural Radiance Fields (ACMMM 2022)
🔥Highlighting the top ML papers every week.
Dense Depth Priors for Neural Radiance Fields from Sparse Input Views
PyTorch Implementation of introducing diffusion approach to 3D depth perception ECCV 2024
A simple pip-installable Python tool to generate your own HTML citation world map from your Google Scholar ID.
A toolbox for benchmarking SOTA discriminative and generative geometry estimation models.
[ECCV'24] GeoWizard: Unleashing the Diffusion Priors for 3D Geometry Estimation from a Single Image
run DROID-SLAM with Metric3D to improve monocular performance
This repo accompanies the research paper, ARKitScenes - A Diverse Real-World Dataset for 3D Indoor Scene Understanding Using Mobile RGB-D Data and contains the data, scripts to visualize and proces…
T-PAMI 2024: G2-MonoDepth: A General Framework of Generalized Depth Inference from Monocular RGB+X Data
[NeurIPS 2024] Depth Anything V2. A More Capable Foundation Model for Monocular Depth Estimation
A fast and simple perlin noise generator using numpy
[ECCV2024 - Oral, Best Paper Award Candidate] SEA-RAFT: Simple, Efficient, Accurate RAFT for Optical Flow
[CVPR'24, Demo Track Honourable Mention] SuperPrimitive: Scene Reconstruction at a Primitive Level
[CVPR24] Depth Prompting for Sensor-Agnostic Depth Estimation
Collection of common code that's shared among different research projects in FAIR computer vision team.
The repo for "Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Image" and "Metric3Dv2: A Versatile Monocular Geometric Foundation Model..."
Universal Monocular Metric Depth Estimation
code for solving global structure from motion problem in the ECCV'14 paper "Robust Global Translations with 1DSfM"
[CVPR'24]🦿GoMVS: Geometrically Consistent Cost Aggregation for Multi-View Stereo
Official code for View Synthesis with Sculpted Neural Points
Offical codes for "GoMAvatar: Efficient Animatable Human Modeling from Monocular Video Using Gaussians-on-Mesh"
Relative Camera Pose Estimation Using Convolutional Neural Networks
[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation
[CVPR 2024 Oral] Rethinking Inductive Biases for Surface Normal Estimation