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Wei Jiang's Projects

aug-nerf icon aug-nerf

[CVPR 2022] "Aug-NeRF: Training Stronger Neural Radiance Fields with Triple-Level Physically-Grounded Augmentations" by Tianlong Chen*, Peihao Wang*, Zhiwen Fan, Zhangyang Wang

bittorrent icon bittorrent

Course project of (2022-2023-2) CS3611@SJTU: Computer Networking.

clipnerf icon clipnerf

CLIP-NeRF: Text-and-Image Driven Manipulation of Neural Radiance Fields

cosypose icon cosypose

Code for "CosyPose: Consistent multi-view multi-object 6D pose estimation", ECCV 2020.

epro-pnp icon epro-pnp

[CVPR 2022 Oral, Best Student Paper] EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation

ganhacks icon ganhacks

starter from "How to Train a GAN?" at NIPS2016

gnerf icon gnerf

[ ICCV 2021 Oral ] Our method can estimate camera poses and neural radiance fields jointly when the cameras are initialized at random poses in complex scenarios (outside-in scenes, even with less texture or intense noise )

ilvr_adm icon ilvr_adm

ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models (ICCV 2021 Oral)

kaldi icon kaldi

kaldi-asr/kaldi is the official location of the Kaldi project.

lapgm icon lapgm

Course project of (2022-2023-1) AI3067@SJTU: Deep Learning and Its Application. Implementation of some graph matching methods, PCA-GM, IPCA-GM, and CIE.

llff icon llff

Code release for Local Light Field Fusion at SIGGRAPH 2019

mine icon mine

Code and models for our ICCV 2021 paper "MINE: Towards Continuous Depth MPI with NeRF for Novel View Synthesis"

mip-nerf-360 icon mip-nerf-360

An implementation of the 2022 paper titled 'Mip-NeRF 360' from Google.

mnist icon mnist

To test the GPU pool uploading.

nerf icon nerf

Code release for NeRF (Neural Radiance Fields)

nerf-pytorch icon nerf-pytorch

A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.

ngp_pl icon ngp_pl

Instant-ngp in pytorch+cuda trained with pytorch-lightning (high quality with high speed, with only few lines of legible code)

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