15 citations · 39 across the 23 of their papers we have counts for
17 papers · 1 filter
Lightweight Generalized DeepFake Face Detection with WAVIE: Wavelet Augmented Vision Intermediate Embeddings
Arya Pulkit, Aditya Ruhela, Akarshan Kapoor +1
Deepfake detection systems often exhibit significant performance degradation when deployed on unseen manipulation methods, limiting their reliability in real-world multimedia envir…
TrackletGPT: A Language-like GPT Framework for White Matter Tract Segmentation
Anoushkrit Goel, Simroop Singh, Ankita Joshi +4
White Matter Tract Segmentation is imperative for studying brain structural connectivity, neurological disorders and neurosurgery. This task remains complex, as tracts differ among…
EAD: An EEG Adapter for Automated Classification
Pushapdeep Singh, Jyoti Nigam, Medicherla Vamsi Krishna +2
While electroencephalography (EEG) has been a popular modality for neural decoding, it often involves task specific acquisition of the EEG data. This poses challenges for the devel…
TractoGPT: A GPT architecture for White Matter Segmentation
Anoushkrit Goel, Simroop Singh, Ankita Joshi +4
White matter bundle segmentation is crucial for studying brain structural connectivity, neurosurgical planning, and neurological disorders. White Matter Segmentation remains challe…
MedSegDiffNCA: Diffusion Models With Neural Cellular Automata for Skin Lesion Segmentation
Avni Mittal, John Kalkhof, Anirban Mukhopadhyay +1
Denoising Diffusion Models (DDMs) are widely used for high-quality image generation and medical image segmentation but often rely on Unet-based architectures, leading to high compu…
TractoEmbed: Modular Multi-level Embedding framework for white matter tract segmentation
Anoushkrit Goel, Bipanjit Singh, Ankita Joshi +4
White matter tract segmentation is crucial for studying brain structural connectivity and neurosurgical planning. However, segmentation remains challenging due to issues like class…
Image Forgery Detection with Interpretability
Ankit Katiyar, Arnav Bhavsar
In this work, we present a learning based method focusing on the convolutional neural network (CNN) architecture to detect these forgeries. We consider the detection of both copy-m…
Detecting Deepfakes with Metric Learning
Akash Kumar, Arnav Bhavsar
With the arrival of several face-swapping applications such as FaceApp, SnapChat, MixBooth, FaceBlender and many more, the authenticity of digital media content is hanging on a ver…
Copy-Move Forgery Classification via Unsupervised Domain Adaptation
Akash Kumar, Arnav Bhavsar
In the current era, image manipulation is becoming increasingly easier, yielding more natural looking images, owing to the modern tools in image processing and computer vision tech…
Role of Class-specific Features in Various Classification Frameworks for Human Epithelial (HEp-2) Cell Images
Vibha Gupta, Arnav Bhavsar
The antinuclear antibody detection with human epithelial cells is a popular approach for autoimmune diseases diagnosis. The manual evaluation demands time, effort and capital, and…
Considerations for a PAP Smear Image Analysis System with CNN Features
Srishti Gautam, Harinarayan K. K., Nirmal Jith +3
It has been shown that for automated PAP-smear image classification, nucleus features can be very informative. Therefore, the primary step for automated screening can be cell-nucle…
Classifying Object Manipulation Actions based on Grasp-types and Motion-Constraints
Kartik Gupta, Darius Burschka, Arnav Bhavsar
In this work, we address a challenging problem of fine-grained and coarse-grained recognition of object manipulation actions. Due to the variations in geometrical and motion constr…
Learning to Decode 7T-like MR Image Reconstruction from 3T MR Images
Aditya Sharma, Prabhjot Kaur, Aditya Nigam +1
Increasing demand for high field magnetic resonance (MR) scanner indicates the need for high-quality MR images for accurate medical diagnosis. However, cost constraints, instead, m…
Siamese LSTM based Fiber Structural Similarity Network (FS2Net) for Rotation Invariant Brain Tractography Segmentation
Shreyas Malakarjun Patil, Aditya Nigam, Arnav Bhavsar +1
In this paper, we propose a novel deep learning architecture combining stacked Bi-directional LSTM and LSTMs with the Siamese network architecture for segmentation of brain fibers,…
Shape Estimation from Defocus Cue for Microscopy Images via Belief Propagation
Arnav Bhavsar
In recent years, the usefulness of 3D shape estimation is being realized in microscopic or close-range imaging, as the 3D information can further be used in various applications. D…
Resolution Enhancement of Range Images via Color-Image Segmentation
Arnav Bhavsar
We report a method for super-resolution of range images. Our approach leverages the interpretation of LR image as sparse samples on the HR grid. Based on this interpretation, we de…
Analysis of Magnification in Depth from Defocus
Arnav Bhavsar
In depth from defocus (DFD), when images are captured with different camera parameters, a relative magnification is induced between them. Image warping is a simpler solution to acc…