Spectral-spatial contrastive clustering (SSCC)
Yaoming Cai, Yan Liu, Zijia Zhang, Zhihua Cai, and Xiaobo Liu, Large-scale Hyperspectral Image Clustering Using Contrastive Learning, 1st CDCEO, CIKM 2021 Workshop
Yaoming Cai, Yan Liu, Zijia Zhang, Zhihua Cai, and Xiaobo Liu, Large-scale Hyperspectral Image Clustering Using Contrastive Learning, 1st CDCEO, CIKM 2021 Workshop
Flask Google Maps Easy to use Google Maps in your Flask application requires Jinja Flask A google api key get here Contribute To contribute with the p
Blockwise Sequential Model Learning Code for 'Blockwise Sequential Model Learning for Partially Observable Reinforcement Learning' (AAAI 2022) For ins
SuperGen The source code for Generating Training Data with Language Models: Towards Zero-Shot Language Understanding. Requirements Before running, you
Hybrid-Supervised Object Detection System Object detection system trained by hybrid-supervision/weakly semi-supervision (HSOD/WSSOD): This project is
deep_autoviml Build keras pipelines and models in a single line of code! Table of Contents Motivation How it works Technology Install Usage API Image
CG-MuAlign A reference implementation for "Collective Multi-type Entity Alignment Between Knowledge Graphs", published in WWW 2020. If you find our pa
Segcache: a memory-efficient and scalable in-memory key-value cache for small objects This repo contains the code of Segcache described in the followi
Official code of Retinal Vessel Segmentation with Pixel-wise Adaptive Filters and Consistency Training (ISBI 2022)
MetaICL: Learning to Learn In Context This includes an original implementation of "MetaICL: Learning to Learn In Context" by Sewon Min, Mike Lewis, Lu
Volume rendering + 3D implicit surface Showcase What? previous: surface rendering; now: volume rendering previous: NeRF's volume density; now: implici
Implicit Feature Alignment: Learn to Convert Text Recognizer to Text Spotter This is a pytorch-based implementation for paper Implicit Feature Alignme
Phy-Q: A Benchmark for Physical Reasoning Cheng Xue*, Vimukthini Pinto*, Chathura Gamage* Ekaterina Nikonova, Peng Zhang, Jochen Renz School of Comput
Neural Turing Machine in Tensorflow Tensorflow implementation of Neural Turing Machine. This implementation uses an LSTM controller. NTM models with m
This is a curated list of tutorials, projects, libraries, videos, papers, books and anything related to the incredible PyTorch. Feel free to make a pu
Contrastive Coding for Active Learning under Class Distribution Mismatch Official PyTorch implementation of ["Contrastive Coding for Active Learning u
generate_cloud_points Given a 2D triangle mesh, we could randomly generate cloud points that fill in the triangle mesh. Run python disp_mesh.py Or you
To run the code Unzip the package to your local directory; Run 'pip install -r requirements.txt' to download required packages; Open file ~/nips_code/
SCCKTIM Weakly Supervised 3D Object Detection from Point Cloud with Only Image-Level Annotation Our code will be available soon. The class knowledge t
The current workflow simulates brain functional connectivity (FC) from structural connectivity (SC) with a neural mass model. Gradient descent is applied to optimize the parameters in the neural mass
nsdf Representing SDFs of arbitrary meshes has been a bit tricky so far. Express