manogna-s Goto Github PK

aad_sfda

Code for our NeurIPS 2022 paper 'Attracting and Dispersing: A Simple Approach for Source-free Domain Adaptation'

cdfsl

clip_prs

official implementation of "Interpreting CLIP's Image Representation via Text-Based Decomposition"

da-fer

Domain Adaptation in Facial Expression Recognition

da-fsl

Domain adaptation and Few shot leaning

manogna-s.github-old

Build a Jekyll blog in minutes, without touching the command line.

manogna-s.github-old.io

Personal website

manogna-s.github.io

A beautiful, simple, clean, and responsive Jekyll theme for academics

meta-dataset

A dataset of datasets for learning to learn from few examples

neglabel

[ICLR 2024 Spotlight] "Negative Label Guided OOD Detection with Pretrained Vision-Language Models"

neuralpainting

owttt

[ICCV 2023 Oral] Official repository for “On the Robustness of Open-World Test-Time Training: Self-Training with Dynamic Prototype Expansion”

promptalign

pstarc

Official code for the paper "pSTarC: Pseudo Source Guided Target Clustering for Fully Test-Time Adaptation"

pytorch-references

rosita

Official code for the paper "Effectiveness of Vision Language Models for Open-world Single Image Test Time Adaptation".

ssa-bns

test-time-adaptation

A repository and benchmark for online test-time adaptation.

tf_to_caffe_conversion

The provided code lets you convert SqueezDet model from a Tensorflow pb file to Caffemodel file

traffic_rlagent

vit-metadataset

Vision Transformers for Cross-domain few shot learning on Meta-Dataset benchmark

vit_cdfsl

Vision Transformers for Cross domain Few shot learning