37 citations · 44 across the 5 of their papers we have counts for
18 papers · 1 filter
Audio-visual video face hallucination with frequency supervision and cross modality support by speech based lip reading loss
Shailza Sharma, Abhinav Dhall, Vinay Kumar +1
Recently, there has been numerous breakthroughs in face hallucination tasks. However, the task remains rather challenging in videos in comparison to the images due to inherent cons…
Frequency Aware Face Hallucination Generative Adversarial Network with Semantic Structural Constraint
Shailza Sharma, Abhinav Dhall, Vinay Kumar
In this paper, we address the issue of face hallucination. Most current face hallucination methods rely on two-dimensional facial priors to generate high resolution face images fro…
Self-Supervised Approach for Facial Movement Based Optical Flow
Muhannad Alkaddour, Usman Tariq, Abhinav Dhall
Computing optical flow is a fundamental problem in computer vision. However, deep learning-based optical flow techniques do not perform well for non-rigid movements such as those f…
FakeBuster: A DeepFakes Detection Tool for Video Conferencing Scenarios
Vineet Mehta, Parul Gupta, Ramanathan Subramanian +1
This paper proposes a new DeepFake detector FakeBuster for detecting impostors during video conferencing and manipulated faces on social media. FakeBuster is a standalone deep lear…
Hyperrealistic Image Inpainting with Hypergraphs
Gourav Wadhwa, Abhinav Dhall, Subrahmanyam Murala +1
Image inpainting is a non-trivial task in computer vision due to multiple possibilities for filling the missing data, which may be dependent on the global information of the image.…
The eyes know it: FakeET -- An Eye-tracking Database to Understand Deepfake Perception
Parul Gupta, Komal Chugh, Abhinav Dhall +1
We present \textbf{FakeET}-- an eye-tracking database to understand human visual perception of \emph{deepfake} videos. Given that the principal purpose of deepfakes is to deceive h…