Search Results for author: Deblina Bhattacharjee

Found 12 papers, 8 papers with code

WiCV@CVPR2024: The Thirteenth Women In Computer Vision Workshop at the Annual CVPR Conference

no code implementations3 Nov 2024 Asra Aslam, Sachini Herath, Ziqi Huang, Estefania Talavera, Deblina Bhattacharjee, Himangi Mittal, Vanessa Staderini, Mengwei Ren, Azade Farshad

In this paper, we present the details of Women in Computer Vision Workshop - WiCV 2024, organized alongside the CVPR 2024 in Seattle, Washington, United States.

Unlocking Comics: The AI4VA Dataset for Visual Understanding

1 code implementation27 Oct 2024 Peter Grönquist, Deblina Bhattacharjee, Bahar Aydemir, Baran Ozaydin, Tong Zhang, Mathieu Salzmann, Sabine Süsstrunk

This dataset is a crucial component of the AI4VA Workshop Challenges~\url{https://sites. google. com/view/ai4vaeccv2024}, where we specifically explore depth and saliency.

Depth Estimation Saliency Detection +1

Data Augmentation via Latent Diffusion for Saliency Prediction

1 code implementation11 Sep 2024 Bahar Aydemir, Deblina Bhattacharjee, Tong Zhang, Mathieu Salzmann, Sabine Süsstrunk

We propose a novel data augmentation method for deep saliency prediction that edits natural images while preserving the complexity and variability of real-world scenes.

Data Augmentation Diversity +2

Vision Transformer Adapters for Generalizable Multitask Learning

no code implementations ICCV 2023 Deblina Bhattacharjee, Sabine Süsstrunk, Mathieu Salzmann

We introduce the first multitasking vision transformer adapters that learn generalizable task affinities which can be applied to novel tasks and domains.

Unsupervised Domain Adaptation

Dense Multitask Learning to Reconfigure Comics

no code implementations16 Jul 2023 Deblina Bhattacharjee, Sabine Süsstrunk, Mathieu Salzmann

In this paper, we develop a MultiTask Learning (MTL) model to achieve dense predictions for comics panels to, in turn, facilitate the transfer of comics from one publication channel to another by assisting authors in the task of reconfiguring their narratives.

Unsupervised Image-To-Image Translation

Estimating Image Depth in the Comics Domain

1 code implementation7 Oct 2021 Deblina Bhattacharjee, Martin Everaert, Mathieu Salzmann, Sabine Süsstrunk

Estimating the depth of comics images is challenging as such images a) are monocular; b) lack ground-truth depth annotations; c) differ across different artistic styles; d) are sparse and noisy.

Depth Estimation Depth Prediction +2

Fidelity Estimation Improves Noisy-Image Classification With Pretrained Networks

1 code implementation1 Jun 2021 Xiaoyu Lin, Deblina Bhattacharjee, Majed El Helou, Sabine Süsstrunk

Furthermore, as proof of concept, we show that when using our oracle fidelity map we even outperform the fully retrained methods, whether trained on noisy or restored images.

Classification Image Classification

Modeling Object Dissimilarity for Deep Saliency Prediction

1 code implementation8 Apr 2021 Bahar Aydemir, Deblina Bhattacharjee, Tong Zhang, Seungryong Kim, Mathieu Salzmann, Sabine Süsstrunk

Saliency prediction has made great strides over the past two decades, with current techniques modeling low-level information, such as color, intensity and size contrasts, and high-level ones, such as attention and gaze direction for entire objects.

Object Prediction +1

DUNIT: Detection-Based Unsupervised Image-to-Image Translation

1 code implementation CVPR 2020 Deblina Bhattacharjee, Seungryong Kim, Guillaume Vizier, Mathieu Salzmann

As evidenced by our experiments, this allows us to outperform the state-of-the-art unsupervised image-to-image translation methods.

Object object-detection +4

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