5 papers
FOCUS: Bridging Fine-Grained Recognition and Open-World Discovery across Domains
Vaibhav Rathore, Divyam Gupta, Moloud Abdar +2
We introduce the first unified framework for *Fine-Grained Domain-Generalized Generalized Category Discovery* (FG-DG-GCD), bringing open-world recognition closer to real-world depl…
CLIPoint3D: Language-Grounded Few-Shot Unsupervised 3D Point Cloud Domain Adaptation
Mainak Singha, Sarthak Mehrotra, Paolo Casari +3
Recent vision-language models (VLMs) such as CLIP demonstrate impressive cross-modal reasoning, extending beyond images to 3D perception. Yet, these models remain fragile under dom…
HIDISC: A Hyperbolic Framework for Domain Generalization with Generalized Category Discovery
Vaibhav Rathore, Divyam Gupta, Biplab Banerjee
Generalized Category Discovery (GCD) aims to classify test-time samples into either seen categories** -- available during training -- or novel ones, without relying on label superv…
When Domain Generalization meets Generalized Category Discovery: An Adaptive Task-Arithmetic Driven Approach
Vaibhav Rathore, Shubhranil B, Saikat Dutta +3
Generalized Class Discovery (GCD) clusters base and novel classes in a target domain using supervision from a source domain with only base classes. Current methods often falter wit…
Few Shot Class Incremental Learning using Vision-Language models
Anurag Kumar, Chinmay Bharti, Saikat Dutta +2
Recent advancements in deep learning have demonstrated remarkable performance comparable to human capabilities across various supervised computer vision tasks. However, the prevale…