implicit-functions

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Here are 14 public repositories matching this topic...

YuliangXiu / ICON

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[CVPR'22] ICON: Implicit Clothed humans Obtained from Normals

Updated Nov 23, 2023
Python

cvg / nice-slam

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[CVPR'22] NICE-SLAM: Neural Implicit Scalable Encoding for SLAM

scalable localization deep-learning slam 3d-reconstruction neural-fields implicit-functions neural-implicit-representations

Updated Mar 10, 2023
Python

Xharlie / pointnerf

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Point-NeRF: Point-based Neural Radiance Fields

Updated Mar 8, 2024
Python

xuchen-ethz / snarf

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Official code release for ICCV 2021 paper SNARF: Differentiable Forward Skinning for Animating Non-rigid Neural Implicit Shapes.

computer-vision neural-network animation computer-graphics 3d iccv 3d-vision skinning implicit-functions iccv2021

Updated May 20, 2023
Python

advimman / CIPS

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Official repository for the paper "Image Generators with Conditionally-Independent Pixel Synthesis" (CVPR2021, Oral)

deep-learning generative-adversarial-network gan implicit-functions foveated-rendering

Updated Feb 19, 2021
Python

PSORLab / EAGO.jl

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A development environment for robust and global optimization

optimization julia optimizer global-optimization robust-optimization optimization-methods optimization-tools mccormick-relaxation implicit-functions

Updated May 1, 2025
Julia

aluo-x / Learning_Neural_Acoustic_Fields

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Official code for "Learning Neural Acoustic Fields" (NeurIPS 2022)

pytorch impulse-response spatial-audio acoustics 3d-audio reverberation acoustic-model acoustic-models neural-fields implicit-functions neural-field spatial-audio-reproduction

Updated Jan 20, 2024
Python

tangjiapeng / SA-ConvONet

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ICCV2021 Oral SA-ConvONet: Sign-Agnostic Optimization of Convolutional Occupancy Networks

surface-reconstruction implicit-functions 3d-shape-reconstruction iccv2021

Updated Apr 13, 2023
Python

Automates steady and unsteady adjoints (general solvers and ODEs respectively). Forward and reverse mode algorithmic differentiation around implicit functions (not propagating AD through), as well as custom rules to allow for mixed-mode AD or calling external (non-AD compatible) functions within an AD chain.

automatic-differentiation algorithmic-differentiation implicit-functions