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pinn-battery-prognostics

State of Health (SoH) and Remaining Useful Life (RUL) prediction for Li-ion batteries based on Physics-Informed Neural Networks (PINN).

pinn_tfi-hss

The code for the paper Temperature field inversion of heat-source systems via physics-informed neural networks

privmrf

An implementation of "Data Synthesis via Differentially Private Markov Random Fields"

rafare

Learning Robust and Accurate Non-parametric 3D Face Reconstruction from Pseudo 2D&3D Pairs (AAAI 2023 Oral)

real2cad-3dv

Shape Matching of Real 3D Object Data to Synthetic 3D CADs (3DV project @ ETHZ)

rq-vae-transformer

The official implementation of Autoregressive Image Generation using Residual Quantization (CVPR '22)

sc2-pcr

SC2-PCR: A Second Order Spatial Compatibility for Efficient and Robust Point Cloud Registration (CVPR 2022)

sc2-pcr-cpp

SC2-PCR c++ version

sc2-pcr-plusplus

scikit-surgery

SciKit-Surgery - Compact Libraries for Surgical Navigation

scr-registration

Code Repository for the paper accepted at MICCAI 2023 "X-Ray to CT Rigid Registration Using Scene Coordinate Regression"

st-evcdp

This is a real-world dataset of 18,061 public electric vehicle (EV) charging piles for spatio-temporal charging demand prediction.

styleformer

[CVPR 2022] Styleformer - Official Pytorch Implementation

synthetic-ct-generation-from-mri-using-3d-transformer-based-denoising-diffusion-model

tfdsunet

TFDSUNet: Time-Frequency Dual-Stream Uncertainty Network for Battery SOH/SOC Prediction

twintex

Official Implementation of TwinTex: Geometry-aware Texture Generation for Abstracted 3D Architectural Models(SIGGRAPH ASIA 2023)

ua-cmdet

This is the official repository for “Drone-based RGB-Infrared Cross-Modality Vehicle Detection via Uncertainty-Aware Learning” (IEEE T-CSVT 2022).

uncertainr

vi-depth

Code for Monocular Visual-Inertial Depth Estimation (ICRA 2023)

x-mrs

Food image / recipe (text) cross-modal representation learning, retrieval and (image) synthesis. Code from ACM-Multimedia 2021 "Cross-Modal Retrieval and Synthesis (X-MRS): Closing the Modality Gap in Shared Representation Learning"