46 citations · 112 across the 13 of their papers we have counts for
17 papers · 1 filter
Doodle It Yourself: Class Incremental Learning by Drawing a Few Sketches
Ayan Kumar Bhunia, Viswanatha Reddy Gajjala, Subhadeep Koley +4
The human visual system is remarkable in learning new visual concepts from just a few examples. This is precisely the goal behind few-shot class incremental learning (FSCIL), where…
Sketching without Worrying: Noise-Tolerant Sketch-Based Image Retrieval
Ayan Kumar Bhunia, Subhadeep Koley, Abdullah Faiz Ur Rahman Khilji +4
Sketching enables many exciting applications, notably, image retrieval. The fear-to-sketch problem (i.e., "I can't sketch") has however proven to be fatal for its widespread adopti…
Partially Does It: Towards Scene-Level FG-SBIR with Partial Input
Pinaki Nath Chowdhury, Ayan Kumar Bhunia, Viswanatha Reddy Gajjala +3
We scrutinise an important observation plaguing scene-level sketch research -- that a significant portion of scene sketches are "partial". A quick pilot study reveals: (i) a scene…
Sketch3T: Test-Time Training for Zero-Shot SBIR
Aneeshan Sain, Ayan Kumar Bhunia, Vaishnav Potlapalli +3
Zero-shot sketch-based image retrieval typically asks for a trained model to be applied as is to unseen categories. In this paper, we question to argue that this setup by definitio…
Joint Visual Semantic Reasoning: Multi-Stage Decoder for Text Recognition
Ayan Kumar Bhunia, Aneeshan Sain, Amandeep Kumar +3
Although text recognition has significantly evolved over the years, state-of-the-art (SOTA) models still struggle in the wild scenarios due to complex backgrounds, varying fonts, u…
Text is Text, No Matter What: Unifying Text Recognition using Knowledge Distillation
Ayan Kumar Bhunia, Aneeshan Sain, Pinaki Nath Chowdhury +1
Text recognition remains a fundamental and extensively researched topic in computer vision, largely owing to its wide array of commercial applications. The challenging nature of th…