2 citations · 4 across the 8 of their papers we have counts for
8 papers
Pulling The REINS: Training-Free Safety Alignment of Video Diffusion Models via Representation Steering
Rohit Kundu, Arindam Dutta, Sarosij Bose +2
Open-weight video diffusion models can generate photorealistic unsafe content, from violence to misinformation, yet existing defenses either require expensive safety fine-tuning th…
SAGA: Source Attribution of Generative AI Videos
Rohit Kundu, Vishal Mohanty, Hao Xiong +3
The proliferation of generative AI has led to hyper-realistic synthetic videos, escalating misuse risks and outstripping binary real/fake detectors. We introduce SAGA (Source Attri…
Towards Source-Free Machine Unlearning
Sk Miraj Ahmed, Umit Yigit Basaran, Dripta S. Raychaudhuri +5
As machine learning becomes more pervasive and data privacy regulations evolve, the ability to remove private or copyrighted information from trained models is becoming an increasi…
FORGE: Forensic Reasoning with Grounded Evidence
Rohit Kundu, Shan Jia, Vishal Mohanty +2
Forensic deepfake analysis demands more than binary classification: investigators need region-grounded natural language explanations they can verify against the image. Multimodal l…
Towards a Universal Synthetic Video Detector: From Face or Background Manipulations to Fully AI-Generated Content
Rohit Kundu, Hao Xiong, Vishal Mohanty +2
Existing DeepFake detection techniques primarily focus on facial manipulations, such as face-swapping or lip-syncing. However, advancements in text-to-video (T2V) and image-to-vide…
Multi-modal Pose Diffuser: A Multimodal Generative Conditional Pose Prior
Calvin-Khang Ta, Arindam Dutta, Rohit Kundu +4
The Skinned Multi-Person Linear (SMPL) model plays a crucial role in 3D human pose estimation, providing a streamlined yet effective representation of the human body. However, ensu…
EarthGen: Generating the World from Top-Down Views
Ansh Sharma, Albert Xiao, Praneet Rathi +4
In this work, we present a novel method for extensive multi-scale generative terrain modeling. At the core of our model is a cascade of superresolution diffusion models that can be…
Repurposing SAM for User-Defined Semantics Aware Segmentation
Rohit Kundu, Sudipta Paul, Arindam Dutta +1
The Segment Anything Model (SAM) excels at generating precise object masks from input prompts but lacks semantic awareness, failing to associate its generated masks with specific o…