Publications de Deblina Bhattacharjee

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Vision Transformer Adapters for Generalizable Multitask Learning

Sabine Süsstrunk, Mathieu Salzmann, Deblina Bhattacharjee

We introduce the first multitasking vision transformer adapters that learn generalizable task affinities which can be applied to novel tasks and domains. Integrated into an off-the-shelf vision transformer backbone, our adapters can simultaneously solve mu ...

2023

Dense Multitask Learning to Reconfigure Comics

Sabine Süsstrunk, Mathieu Salzmann, Deblina Bhattacharjee

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

IEEE2023

MulT: An End-to-End Multitask Learning Transformer

Sabine Süsstrunk, Mathieu Salzmann, Tong Zhang, Deblina Bhattacharjee

We propose an end-to-end Multitask Learning Transformer framework, named MulT, to simultaneously learn multiple high-level vision tasks, including depth estimation, semantic segmentation, reshading, surface normal estimation, 2D keypoint detection, and edg ...

2022

Modeling Object Dissimilarity for Deep Saliency Prediction

Sabine Süsstrunk, Mathieu Salzmann, Tong Zhang, Bahar Aydemir, Seungryong Kim, Deblina Bhattacharjee

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. Despit ...

2022

Estimating Image Depth in the Comics Domain

Sabine Süsstrunk, Mathieu Salzmann, Martin Nicolas Everaert, Deblina Bhattacharjee

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. We thus, use an off-the-shelf unsupervised image to image tra ...

2021

Deblina Bhattacharjee

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