6 papers
PromptSync: Bridging Domain Gaps in Vision-Language Models through Class-Aware Prototype Alignment and Discrimination
Anant Khandelwal
The potential for zero-shot generalization in vision-language (V-L) models such as CLIP has spurred their widespread adoption in addressing numerous downstream tasks. Previous meth…
SegDA: Maximum Separable Segment Mask with Pseudo Labels for Domain Adaptive Semantic Segmentation
Anant Khandelwal
Unsupervised Domain Adaptation (UDA) aims to solve the problem of label scarcity of the target domain by transferring the knowledge from the label rich source domain. Usually, the…
InFusion: Inject and Attention Fusion for Multi Concept Zero-Shot Text-based Video Editing
Anant Khandelwal
Large text-to-image diffusion models have achieved remarkable success in generating diverse, high-quality images. Additionally, these models have been successfully leveraged to edi…
Large Scale Generative Multimodal Attribute Extraction for E-commerce Attributes
Anant Khandelwal, Happy Mittal, Shreyas Sunil Kulkarni +1
E-commerce websites (e.g. Amazon) have a plethora of structured and unstructured information (text and images) present on the product pages. Sellers often either don't label or mis…
DomainInv: Domain Invariant Fine Tuning and Adversarial Label Correction For QA Domain Adaptation
Anant Khandelwal
Existing Question Answering (QA) systems limited by the capability of answering questions from unseen domain or any out-of-domain distributions making them less reliable for deploy…
MASIL: Towards Maximum Separable Class Representation for Few Shot Class Incremental Learning
Anant Khandelwal
Few Shot Class Incremental Learning (FSCIL) with few examples per class for each incremental session is the realistic setting of continual learning since obtaining large number of…