6 citations · 31 across the 24 of their papers we have counts for
25 papers
HINT-Blimp: Human INTent Inference from Multimodal Cues for Robotic Blimps
Subhadeep Koley, Benjamin Greenberg, Yifei Simon Shao +3
In human-robot interaction, traditional interfaces such as joysticks and handheld tablets introduce latency into navigation tasks and require the operator's explicit attention on t…
Planning Trajectories that Bounce: Reflection Classes for Collision-Tolerant Robots
Subhadeep Koley, Subhrajit Bhattacharya, David Saldaña
Robot navigation methods tend to avoid contact, and consequently search for collision-free trajectories. For robots with high inertia and limited maneuverability, however, avoiding…
Training-free Temporal Object Tracking in Surgical Videos
Subhadeep Koley, Abdolrahim Kadkhodamohammadi, Santiago Barbarisi +2
Purpose: In this paper, we present a novel approach for online object tracking in laparoscopic cholecystectomy (LC) surgical videos, targeting localisation and tracking of critical…
Doodle Your Keypoints: Sketch-Based Few-Shot Keypoint Detection
Subhajit Maity, Ayan Kumar Bhunia, Subhadeep Koley +3
Keypoint detection, integral to modern machine perception, faces challenges in few-shot learning, particularly when source data from the same distribution as the query is unavailab…
Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch
Aneeshan Sain, Subhajit Maity, Pinaki Nath Chowdhury +3
As sketch research has collectively matured over time, its adaptation for at-mass commercialisation emerges on the immediate horizon. Despite an already mature research endeavour f…
SketchFusion: Learning Universal Sketch Features through Fusing Foundation Models
Subhadeep Koley, Tapas Kumar Dutta, Aneeshan Sain +3
While foundation models have revolutionised computer vision, their effectiveness for sketch understanding remains limited by the unique challenges of abstract, sparse visual inputs…
SketchYourSeg: Mask-Free Subjective Image Segmentation via Freehand Sketches
Subhadeep Koley, Viswanatha Reddy Gajjala, Aneeshan Sain +4
We introduce SketchYourSeg, a novel framework that establishes freehand sketches as a powerful query modality for subjective image segmentation across entire galleries through a si…
DreamColour: Controllable Video Colour Editing without Training
Chaitat Utintu, Pinaki Nath Chowdhury, Aneeshan Sain +3
Video colour editing is a crucial task for content creation, yet existing solutions either require painstaking frame-by-frame manipulation or produce unrealistic results with tempo…
Do Generalised Classifiers really work on Human Drawn Sketches?
Hmrishav Bandyopadhyay, Pinaki Nath Chowdhury, Aneeshan Sain +4
This paper, for the first time, marries large foundation models with human sketch understanding. We demonstrate what this brings -- a paradigm shift in terms of generalised sketch…
Freeview Sketching: View-Aware Fine-Grained Sketch-Based Image Retrieval
Aneeshan Sain, Pinaki Nath Chowdhury, Subhadeep Koley +2
In this paper, we delve into the intricate dynamics of Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) by addressing a critical yet overlooked aspect -- the choice of viewpoint…
SketchDeco: Training-Free Latent Composition for Precise Sketch Colourisation
Chaitat Utintu, Yi-Zhe Song
We introduce SketchDeco, a training-free approach to sketch colourisation that bridges the gap between professional design needs and intuitive, region-based control. Our method emp…
It's All About Your Sketch: Democratising Sketch Control in Diffusion Models
Subhadeep Koley, Ayan Kumar Bhunia, Deeptanshu Sekhri +4
This paper unravels the potential of sketches for diffusion models, addressing the deceptive promise of direct sketch control in generative AI. We importantly democratise the proce…
You'll Never Walk Alone: A Sketch and Text Duet for Fine-Grained Image Retrieval
Subhadeep Koley, Ayan Kumar Bhunia, Aneeshan Sain +3
Two primary input modalities prevail in image retrieval: sketch and text. While text is widely used for inter-category retrieval tasks, sketches have been established as the sole p…
Text-to-Image Diffusion Models are Great Sketch-Photo Matchmakers
Subhadeep Koley, Ayan Kumar Bhunia, Aneeshan Sain +3
This paper, for the first time, explores text-to-image diffusion models for Zero-Shot Sketch-based Image Retrieval (ZS-SBIR). We highlight a pivotal discovery: the capacity of text…
How to Handle Sketch-Abstraction in Sketch-Based Image Retrieval?
Subhadeep Koley, Ayan Kumar Bhunia, Aneeshan Sain +3
In this paper, we propose a novel abstraction-aware sketch-based image retrieval framework capable of handling sketch abstraction at varied levels. Prior works had mainly focused o…
DemoCaricature: Democratising Caricature Generation with a Rough Sketch
Dar-Yen Chen, Ayan Kumar Bhunia, Subhadeep Koley +3
In this paper, we democratise caricature generation, empowering individuals to effortlessly craft personalised caricatures with just a photo and a conceptual sketch. Our objective…
Doodle Your 3D: From Abstract Freehand Sketches to Precise 3D Shapes
Hmrishav Bandyopadhyay, Subhadeep Koley, Ayan Das +5
In this paper, we democratise 3D content creation, enabling precise generation of 3D shapes from abstract sketches while overcoming limitations tied to drawing skills. We introduce…
Sketch2Saliency: Learning to Detect Salient Objects from Human Drawings
Ayan Kumar Bhunia, Subhadeep Koley, Amandeep Kumar +4
Human sketch has already proved its worth in various visual understanding tasks (e.g., retrieval, segmentation, image-captioning, etc). In this paper, we reveal a new trait of sket…
Picture that Sketch: Photorealistic Image Generation from Abstract Sketches
Subhadeep Koley, Ayan Kumar Bhunia, Aneeshan Sain +3
Given an abstract, deformed, ordinary sketch from untrained amateurs like you and me, this paper turns it into a photorealistic image - just like those shown in Fig. 1(a), all non-…
CLIP for All Things Zero-Shot Sketch-Based Image Retrieval, Fine-Grained or Not
Aneeshan Sain, Ayan Kumar Bhunia, Pinaki Nath Chowdhury +3
In this paper, we leverage CLIP for zero-shot sketch based image retrieval (ZS-SBIR). We are largely inspired by recent advances on foundation models and the unparalleled generalis…
Exploiting Unlabelled Photos for Stronger Fine-Grained SBIR
Aneeshan Sain, Ayan Kumar Bhunia, Subhadeep Koley +4
This paper advances the fine-grained sketch-based image retrieval (FG-SBIR) literature by putting forward a strong baseline that overshoots prior state-of-the-arts by ~11%. This is…
What Can Human Sketches Do for Object Detection?
Pinaki Nath Chowdhury, Ayan Kumar Bhunia, Aneeshan Sain +3
Sketches are highly expressive, inherently capturing subjective and fine-grained visual cues. The exploration of such innate properties of human sketches has, however, been limited…
SceneTrilogy: On Human Scene-Sketch and its Complementarity with Photo and Text
Pinaki Nath Chowdhury, Ayan Kumar Bhunia, Aneeshan Sain +3
In this paper, we extend scene understanding to include that of human sketch. The result is a complete trilogy of scene representation from three diverse and complementary modaliti…
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…