scottjingtt Goto Github PK

amf_gzs_sbir

Implementation of AMF for GZS-SBIR

apn-zsl

This is a PyTorch implementation of the paper "Attribute Prototype Network for Zero-Shot Learning".

awesome-domain-adaptation

A collection of AWESOME things about domian adaptation

awesome-explainable-ai

A collection of research materials on explainable AI/ML

awesome-interpretable-transfer-learning

Paper and resources collections about interpretable AI (XAI)

awesome-open-vocabulary-segmentation

A collection of AWESOME things about open-vocabulary segmentation

bddoia_project

cdtrans

[ICLR2022] CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation

dynamic-vision-transformer

Accelerating T2t-ViT by 1.6-3.6x.

evidential-deep-learning

Learn fast, scalable, and calibrated measures of uncertainty using neural networks!

explaining-in-style

inaction

Implementation of the paper InAction, ECCV 2022

led2-net

CVPR 2021 Oral paper "LED2-Net: Monocular 360˚ Layout Estimation via Differentiable Depth Rendering" official PyTorch implementation.

leetcode_company_frequency

Collection of leetcode company tag problems. Periodically updating.

leetcode_company_wise_questions

This is a repository containing the list of company wise questions available on leetcode premium

lgt-net

This is PyTorch implementation of our paper "LGT-Net: Indoor Panoramic Room Layout Estimation with Geometry-Aware Transformer Network".(CVPR'22)

machine-learning-from-scratch

Implementation of popular ML algorithms from scratch

maf

Code and supplementary materials for MAF "Marginalized Augmented Few-shot Domain Adaptation"

mvit

Code Release for MViTv2 on Image Recognition.

notes

Personal Notes

pedestrian_intent_action_detection

Code for our paper "Coupling Intent and Action for Pedestrian Crossing Behavior Prediction"

protoprop

Code for the NeurIPS 2021 paper "Independent Prototype Propagation for Zero-Shot Compositionality"

pvt

pytorch-gan

PyTorch implementations of Generative Adversarial Networks.

scottjingtt.github.io

Scott's Homepage

sdat

Source code for "A Closer Look at Smoothness in Domain Adversarial Training", ICML 2022

shot-plus

code for our paper "Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer"

smile-mocap

Tools for motion capture data. Data collection was captured by a Vicon system and Kinect Sensor in SMILE Lab, NEU.

srosda

implementation of the ICCV work "SR-OSDA"

stereo-360-layout