Publications

2024

1. IDD-AW: A Benchmark for Safe and Robust Segmentation of Drive Scenes in Unstructured Traffic and Adverse Weather

   Furqan Ahmed Shaik, Abhishek Reddy, Nikhil Reddy Billa, and 3 more authors

   In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) , Jan 2024

   Bib

   @inproceedings{Shaik_2024_WACV,
     author = {Shaik, Furqan Ahmed and Reddy, Abhishek and Billa, Nikhil Reddy and Chaudhary, Kunal and Manchanda, Sunny and Varma, Girish},
     title = {IDD-AW: A Benchmark for Safe and Robust Segmentation of Drive Scenes in Unstructured Traffic and Adverse Weather},
     booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
     month = jan,
     year = {2024},
     pages = {4614-4623},
   }

2. CNN based image resizing forensics for double compressed JPEG images

   Nikhil Reddy Billa, Bibhash Pran Das, Mrutyunjay Biswal, and 1 more author

   Journal of Information Security and Applications, Jan 2024

   Abs Bib

   This paper investigates a novel CNN-based architecture for image resizing forensics in the presence of Double-JPEG compression. Two sub-problems are addressed as part of this paper: first, the detection of resizing in DJPEG images, and second, determining the factor used to resize the image before the second JPEG compression. The image resizing technique used in this paper is image scaling. The proposed network is based on utilizing specially chosen high pass filters that constitute the pre-processing layer, followed by four convolutional layers, two fully connected layers, and a final softmax layer. The high-pass filters preserve the resizing clues in the form of residuals applied at the pre-processing layer, followed by utilizing the residuals as inputs to a CNN to detect the presence of resizing and also for estimating the resizing factor. The proposed network is fully end-to-end and does not rely on any hand-crafting. Experimental validation is carried out utilizing images from the RAISE dataset. Comparative analysis with four state-of-the-art methods demonstrates the proposed CNN-based architecture’s superiority for resizing detection and resize factor determination sub-problems.

   @article{BILLA2024103693,
     title = {CNN based image resizing forensics for double compressed JPEG images},
     journal = {Journal of Information Security and Applications},
     volume = {81},
     pages = {103693},
     year = {2024},
     issn = {2214-2126},
     doi = {https://doi.org/10.1016/j.jisa.2023.103693},
     url = {https://www.sciencedirect.com/science/article/pii/S2214212623002776},
     author = {Billa, Nikhil Reddy and Das, Bibhash Pran and Biswal, Mrutyunjay and Okade, Manish},
     keywords = {Image resizing forensics, Double-JPEG, CNN model, Image scaling, High pass filters},
   }