4 papers
Fully Unsupervised Self-debiasing of Text-to-Image Diffusion Models
Korada Sri Vardhana, Shrikrishna Lolla, Soma Biswas
Text-to-image (T2I) diffusion models have achieved widespread success due to their ability to generate high-resolution, photorealistic images. These models are trained on large-sca…
Segmentation Assisted Incremental Test Time Adaptation in an Open World
Manogna Sreenivas, Soma Biswas
In dynamic environments, unfamiliar objects and distribution shifts are often encountered, which challenge the generalization abilities of the deployed trained models. This work ad…
Efficient Open Set Single Image Test Time Adaptation of Vision Language Models
Manogna Sreenivas, Soma Biswas
Adapting models to dynamic, real-world environments characterized by shifting data distributions and unseen test scenarios is a critical challenge in deep learning. In this paper,…
pSTarC: Pseudo Source Guided Target Clustering for Fully Test-Time Adaptation
Manogna Sreenivas, Goirik Chakrabarty, Soma Biswas
Test Time Adaptation (TTA) is a pivotal concept in machine learning, enabling models to perform well in real-world scenarios, where test data distribution differs from training. In…