3 citations · 11 across the 30 of their papers we have counts for
25 papers · 1 filter
When, Where, and Why: Hierarchical Causal Explainability for Video Face Understanding with MLLMs
Anubhav Kataria, Shreya Ghosh, Jingwen Ye +1
Understanding facial behaviour in video requires answering three fundamental questions: when a key facial expression occurs, where the model attends on the face at that moment, and…
Explainable Deepfake Detection Challenge
Abhijeet Narang, Kartik Kuckreja, Shreya Ghosh +4
Deepfake detection is moving beyond binary classification decisions toward systems that can also explain the visual evidence supporting those decisions. This transition is importan…
XPlainVerse: A Million-Scale Benchmark for Explainable Deepfake Detection
Abhijeet Narang, Kartik Kuckreja, Shreya Ghosh +3
As deepfake detection models increasingly produce natural language explanations, their reasoning often remains weakly grounded in visual artifacts, limiting reliability and user tr…
Pixels Don't Lie (But Your Detector Might): Bootstrapping MLLM-as-a-Judge for Trustworthy Deepfake Detection and Reasoning Supervision
Kartik Kuckreja, Parul Gupta, Muhammad Haris Khan +1
Deepfake detection models often generate natural-language explanations, yet their reasoning is frequently ungrounded in visual evidence, limiting reliability. Existing evaluations…
VFace: A Training-Free Approach for Diffusion-Based Video Face Swapping
Sanoojan Baliah, Yohan Abeysinghe, Rusiru Thushara +4
We present a training-free, plug-and-play method, namely VFace, for high-quality face swapping in videos. It can be seamlessly integrated with image-based face swapping approaches…
A Survey of Body and Face Motion: Datasets, Performance Evaluation Metrics and Generative Techniques
Lownish Rai Sookha, Nikhil Pakhale, Mudasir Ganaie +1
Body and face motion play an integral role in communication. They convey crucial information on the participants. Advances in generative modeling and multi-modal learning have enab…
CSGaze: Context-aware Social Gaze Prediction
Surbhi Madan, Shreya Ghosh, Ramanathan Subramanian +2
A person's gaze offers valuable insights into their focus of attention, level of social engagement, and confidence. In this work, we investigate how contextual cues combined with v…
SFANet: Spatial-Frequency Attention Network for Deepfake Detection
Vrushank Ahire, Aniruddh Muley, Shivam Zample +4
Detecting manipulated media has now become a pressing issue with the recent rise of deepfakes. Most existing approaches fail to generalize across diverse datasets and generation te…
SynchroRaMa : Lip-Synchronized and Emotion-Aware Talking Face Generation via Multi-Modal Emotion Embedding
Phyo Thet Yee, Dimitrios Kollias, Sudeepta Mishra +1
Audio-driven talking face generation has received growing interest, particularly for applications requiring expressive and natural human-avatar interaction. However, most existing…
AV-Deepfake1M++: A Large-Scale Audio-Visual Deepfake Benchmark with Real-World Perturbations
Zhixi Cai, Kartik Kuckreja, Shreya Ghosh +5
The rapid surge of text-to-speech and face-voice reenactment models makes video fabrication easier and highly realistic. To encounter this problem, we require datasets that rich in…
Improving Personalized Image Generation through Social Context Feedback
Parul Gupta, Abhinav Dhall, Thanh-Toan Do
Personalized image generation, where reference images of one or more subjects are used to generate their image according to a scene description, has gathered significant interest i…
Gems: Group Emotion Profiling Through Multimodal Situational Understanding
Anubhav Kataria, Surbhi Madan, Shreya Ghosh +2
Understanding individual, group and event level emotions along with contextual information is crucial for analyzing a multi-person social situation. To achieve this, we frame emoti…
Tell me Habibi, is it Real or Fake?
Kartik Kuckreja, Parul Gupta, Injy Hamed +3
Deepfake generation methods are evolving fast, making fake media harder to detect and raising serious societal concerns. Most deepfake detection and dataset creation research focus…
A Cycle Ride to HDR: Semantics Aware Self-Supervised Framework for Unpaired LDR-to-HDR Image Reconstruction
Hrishav Bakul Barua, Kalin Stefanov, Lemuel Lai En Che +3
Reconstruction of High Dynamic Range (HDR) from Low Dynamic Range (LDR) images is an important computer vision task. There is a significant amount of research utilizing both conven…
MRAC Track 1: 2nd Workshop on Multimodal, Generative and Responsible Affective Computing
Shreya Ghosh, Zhixi Cai, Abhinav Dhall +3
With the rapid advancements in multimodal generative technology, Affective Computing research has provoked discussion about the potential consequences of AI systems equipped with e…
1M-Deepfakes Detection Challenge
Zhixi Cai, Abhinav Dhall, Shreya Ghosh +4
The detection and localization of deepfake content, particularly when small fake segments are seamlessly mixed with real videos, remains a significant challenge in the field of dig…
MIP-GAF: A MLLM-annotated Benchmark for Most Important Person Localization and Group Context Understanding
Surbhi Madan, Shreya Ghosh, Lownish Rai Sookha +4
Estimating the Most Important Person (MIP) in any social event setup is a challenging problem mainly due to contextual complexity and scarcity of labeled data. Moreover, the causal…
A Survey of Deep Learning for Group-level Emotion Recognition
Xiaohua Huang, Jinke Xu, Wenming Zheng +2
With the advancement of artificial intelligence (AI) technology, group-level emotion recognition (GER) has emerged as an important area in analyzing human behavior. Early GER metho…
7th ABAW Competition: Multi-Task Learning and Compound Expression Recognition
Dimitrios Kollias, Stefanos Zafeiriou, Irene Kotsia +4
This paper describes the 7th Affective Behavior Analysis in-the-wild (ABAW) Competition, which is part of the respective Workshop held in conjunction with ECCV 2024. The 7th ABAW C…
Conditional Distribution Modelling for Few-Shot Image Synthesis with Diffusion Models
Parul Gupta, Munawar Hayat, Abhinav Dhall +1
Few-shot image synthesis entails generating diverse and realistic images of novel categories using only a few example images. While multiple recent efforts in this direction have a…
Real, fake and synthetic faces -- does the coin have three sides?
Shahzeb Naeem, Ramzi Al-Sharawi, Muhammad Riyyan Khan +3
With the ever-growing power of generative artificial intelligence, deepfake and artificially generated (synthetic) media have continued to spread online, which creates various ethi…
Generation and Detection of Sign Language Deepfakes - A Linguistic and Visual Analysis
Shahzeb Naeem, Muhammad Riyyan Khan, Usman Tariq +3
This research explores the positive application of deepfake technology for upper body generation, specifically sign language for the Deaf and Hard of Hearing (DHoH) community. Give…
GTA-HDR: A Large-Scale Synthetic Dataset for HDR Image Reconstruction
Hrishav Bakul Barua, Kalin Stefanov, KokSheik Wong +2
High Dynamic Range (HDR) content (i.e., images and videos) has a broad range of applications. However, capturing HDR content from real-world scenes is expensive and time-consuming.…
DiffAugment: Diffusion based Long-Tailed Visual Relationship Recognition
Parul Gupta, Tuan Nguyen, Abhinav Dhall +3
The task of Visual Relationship Recognition (VRR) aims to identify relationships between two interacting objects in an image and is particularly challenging due to the widely-sprea…