Search Results for author: Pinaki Nath Chowdhury

Found 37 papers, 15 papers with code

Freestyle Sketch-in-the-Loop Image Segmentation

no code implementations27 Jan 2025 Subhadeep Koley, Viswanatha Reddy Gajjala, Aneeshan Sain, Pinaki Nath Chowdhury, Tao Xiang, Ayan Kumar Bhunia, Yi-Zhe Song

In this paper, we expand the domain of sketch research into the field of image segmentation, aiming to establish freehand sketches as a query modality for subjective image segmentation.

Image Segmentation Segmentation +2

DreamColour: Controllable Video Colour Editing without Training

1 code implementation6 Dec 2024 Chaitat Utintu, Pinaki Nath Chowdhury, Aneeshan Sain, Subhadeep Koley, Ayan Kumar Bhunia, Yi-Zhe Song

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 temporal artefacts.

Instance Segmentation Semantic Segmentation

Do Generalised Classifiers really work on Human Drawn Sketches?

1 code implementation4 Jul 2024 Hmrishav Bandyopadhyay, Pinaki Nath Chowdhury, Aneeshan Sain, Subhadeep Koley, Tao Xiang, Ayan Kumar Bhunia, Yi-Zhe Song

This generalisation happens on two fronts: (i) generalisation across unknown categories (i. e., open-set), and (ii) generalisation traversing abstraction levels (i. e., good and bad sketches), both being timely challenges that remain unsolved in the sketch literature.

Representation Learning

Freeview Sketching: View-Aware Fine-Grained Sketch-Based Image Retrieval

no code implementations1 Jul 2024 Aneeshan Sain, Pinaki Nath Chowdhury, Subhadeep Koley, Ayan Kumar Bhunia, Yi-Zhe Song

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 during sketch creation.

Disentanglement Retrieval +1

SketchDeco: Decorating B&W Sketches with Colour

1 code implementation29 May 2024 Chaitat Utintu, Pinaki Nath Chowdhury, Aneeshan Sain, Subhadeep Koley, Ayan Kumar Bhunia, Yi-Zhe Song

This paper introduces a novel approach to sketch colourisation, inspired by the universal childhood activity of colouring and its professional applications in design and story-boarding.

Image Generation Sketch Colorization

What Sketch Explainability Really Means for Downstream Tasks

no code implementations14 Mar 2024 Hmrishav Bandyopadhyay, Pinaki Nath Chowdhury, Ayan Kumar Bhunia, Aneeshan Sain, Tao Xiang, Yi-Zhe Song

In this paper, we explore the unique modality of sketch for explainability, emphasising the profound impact of human strokes compared to conventional pixel-oriented studies.

Retrieval

SketchINR: A First Look into Sketches as Implicit Neural Representations

1 code implementation CVPR 2024 Hmrishav Bandyopadhyay, Ayan Kumar Bhunia, Pinaki Nath Chowdhury, Aneeshan Sain, Tao Xiang, Timothy Hospedales, Yi-Zhe Song

(ii) SketchINR's auto-decoder provides a much higher-fidelity representation than other learned vector sketch representations, and is uniquely able to scale to complex vector sketches such as FS-COCO.

Data Compression Decoder

What Sketch Explainability Really Means for Downstream Tasks?

no code implementations CVPR 2024 Hmrishav Bandyopadhyay, Pinaki Nath Chowdhury, Ayan Kumar Bhunia, Aneeshan Sain, Tao Xiang, Yi-Zhe Song

In this paper we explore the unique modality of sketch for explainability emphasising the profound impact of human strokes compared to conventional pixel-oriented studies.

Retrieval

Doodle Your 3D: From Abstract Freehand Sketches to Precise 3D Shapes

1 code implementation CVPR 2024 Hmrishav Bandyopadhyay, Subhadeep Koley, Ayan Das, Ayan Kumar Bhunia, Aneeshan Sain, Pinaki Nath Chowdhury, Tao Xiang, Yi-Zhe Song

In this paper, we democratise 3D content creation, enabling precise generation of 3D shapes from abstract sketches while overcoming limitations tied to drawing skills.

Decoder Position

DemoCaricature: Democratising Caricature Generation with a Rough Sketch

no code implementations CVPR 2024 Dar-Yen Chen, Ayan Kumar Bhunia, Subhadeep Koley, Aneeshan Sain, Pinaki Nath Chowdhury, Yi-Zhe Song

In this paper, we democratise caricature generation, empowering individuals to effortlessly craft personalised caricatures with just a photo and a conceptual sketch.

Caricature Model Editing

What Can Human Sketches Do for Object Detection?

no code implementations CVPR 2023 Pinaki Nath Chowdhury, Ayan Kumar Bhunia, Aneeshan Sain, Subhadeep Koley, Tao Xiang, Yi-Zhe Song

In particular, we first perform independent prompting on both sketch and photo branches of an SBIR model to build highly generalisable sketch and photo encoders on the back of the generalisation ability of CLIP.

Object object-detection +3

Exploiting Unlabelled Photos for Stronger Fine-Grained SBIR

no code implementations CVPR 2023 Aneeshan Sain, Ayan Kumar Bhunia, Subhadeep Koley, Pinaki Nath Chowdhury, Soumitri Chattopadhyay, Tao Xiang, Yi-Zhe Song

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%.

Knowledge Distillation Sketch-Based Image Retrieval +1

Picture that Sketch: Photorealistic Image Generation from Abstract Sketches

no code implementations CVPR 2023 Subhadeep Koley, Ayan Kumar Bhunia, Aneeshan Sain, Pinaki Nath Chowdhury, Tao Xiang, Yi-Zhe Song

We further introduce specific designs to tackle the abstract nature of human sketches, including a fine-grained discriminative loss on the back of a trained sketch-photo retrieval model, and a partial-aware sketch augmentation strategy.

Decoder Image Generation +2

Democratising 2D Sketch to 3D Shape Retrieval Through Pivoting

no code implementations ICCV 2023 Pinaki Nath Chowdhury, Ayan Kumar Bhunia, Aneeshan Sain, Subhadeep Koley, Tao Xiang, Yi-Zhe Song

We perform pivoting on two existing datasets, each from a distant research domain to the other: 2D sketch and photo pairs from the sketch-based image retrieval field (SBIR), and 3D shapes from ShapeNet.

3D Shape Retrieval Retrieval +1

Adaptive Fine-Grained Sketch-Based Image Retrieval

1 code implementation4 Jul 2022 Ayan Kumar Bhunia, Aneeshan Sain, Parth Shah, Animesh Gupta, Pinaki Nath Chowdhury, Tao Xiang, Yi-Zhe Song

To solve this new problem, we introduce a novel model-agnostic meta-learning (MAML) based framework with several key modifications: (1) As a retrieval task with a margin-based contrastive loss, we simplify the MAML training in the inner loop to make it more stable and tractable.

Meta-Learning Retrieval +1

Sketch3T: Test-Time Training for Zero-Shot SBIR

no code implementations CVPR 2022 Aneeshan Sain, Ayan Kumar Bhunia, Vaishnav Potlapalli, Pinaki Nath Chowdhury, Tao Xiang, Yi-Zhe Song

In this paper, we question to argue that this setup by definition is not compatible with the inherent abstract and subjective nature of sketches, i. e., the model might transfer well to new categories, but will not understand sketches existing in different test-time distribution as a result.

Meta-Learning Retrieval +1

SketchLattice: Latticed Representation for Sketch Manipulation

no code implementations ICCV 2021 Yonggang Qi, Guoyao Su, Pinaki Nath Chowdhury, Mingkang Li, Yi-Zhe Song

The key challenge in designing a sketch representation lies with handling the abstract and iconic nature of sketches.

Text is Text, No Matter What: Unifying Text Recognition using Knowledge Distillation

no code implementations ICCV 2021 Ayan Kumar Bhunia, Aneeshan Sain, Pinaki Nath Chowdhury, Yi-Zhe Song

In this paper, for the first time, we argue for their unification -- we aim for a single model that can compete favourably with two separate state-of-the-art STR and HTR models.

Handwriting Recognition HTR +2

Towards the Unseen: Iterative Text Recognition by Distilling from Errors

no code implementations ICCV 2021 Ayan Kumar Bhunia, Pinaki Nath Chowdhury, Aneeshan Sain, Yi-Zhe Song

Our framework is iterative in nature, in that it utilises predicted knowledge of character sequences from a previous iteration, to augment the main network in improving the next prediction.

MetaHTR: Towards Writer-Adaptive Handwritten Text Recognition

1 code implementation CVPR 2021 Ayan Kumar Bhunia, Shuvozit Ghose, Amandeep Kumar, Pinaki Nath Chowdhury, Aneeshan Sain, Yi-Zhe Song

In this paper, we take a completely different perspective -- we work on the assumption that there is always a new style that is drastically different, and that we will only have very limited data during testing to perform adaptation.

Handwritten Text Recognition HTR +1

More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval

1 code implementation CVPR 2021 Ayan Kumar Bhunia, Pinaki Nath Chowdhury, Aneeshan Sain, Yongxin Yang, Tao Xiang, Yi-Zhe Song

A fundamental challenge faced by existing Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) models is the data scarcity -- model performances are largely bottlenecked by the lack of sketch-photo pairs.

Cross-Modal Retrieval Retrieval +2

UDBNET: Unsupervised Document Binarization Network via Adversarial Game

1 code implementation14 Jul 2020 Amandeep Kumar, Shuvozit Ghose, Pinaki Nath Chowdhury, Partha Pratim Roy, Umapada Pal

In this paper, we present a novel approach towards document image binarization by introducing three-player min-max adversarial game.

Binarization

Modeling Extent-of-Texture Information for Ground Terrain Recognition

1 code implementation17 Apr 2020 Shuvozit Ghose, Pinaki Nath Chowdhury, Partha Pratim Roy, Umapada Pal

Ground Terrain Recognition is a difficult task as the context information varies significantly over the regions of a ground terrain image.

Image Classification

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