179 citations · 424 across the 12 of their papers we have counts for
28 papers · 1 filter
DocEnTr: An End-to-End Document Image Enhancement Transformer
Mohamed Ali Souibgui, Sanket Biswas, Sana Khamekhem Jemni +4
Document images can be affected by many degradation scenarios, which cause recognition and processing difficulties. In this age of digitization, it is important to denoise them for…
LoOp: Looking for Optimal Hard Negative Embeddings for Deep Metric Learning
Bhavya Vasudeva, Puneesh Deora, Saumik Bhattacharya +2
Deep metric learning has been effectively used to learn distance metrics for different visual tasks like image retrieval, clustering, etc. In order to aid the training process, exi…
Graph-based Deep Generative Modelling for Document Layout Generation
Sanket Biswas, Pau Riba, Josep Lladós +1
One of the major prerequisites for any deep learning approach is the availability of large-scale training data. When dealing with scanned document images in real world scenarios, t…
DocSynth: A Layout Guided Approach for Controllable Document Image Synthesis
Sanket Biswas, Pau Riba, Josep Lladós +1
Despite significant progress on current state-of-the-art image generation models, synthesis of document images containing multiple and complex object layouts is a challenging task.…
PLSM: A Parallelized Liquid State Machine for Unintentional Action Detection
Dipayan Das, Saumik Bhattacharya, Umapada Pal +1
Reservoir Computing (RC) offers a viable option to deploy AI algorithms on low-end embedded system platforms. Liquid State Machine (LSM) is a bio-inspired RC model that mimics the…
AIM 2020 Challenge on Learned Image Signal Processing Pipeline
Andrey Ignatov, Radu Timofte, Zhilu Zhang +36
This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results. The participating teams were solving a real-world RAW-to…