21 citations · 29 across the 9 of their papers we have counts for
10 papers · 1 filter
MultLFG: Training-free Multi-LoRA composition using Frequency-domain Guidance
Aniket Roy, Maitreya Suin, Ketul Shah +1
Low-Rank Adaptation (LoRA) has gained prominence as a computationally efficient method for fine-tuning generative models, enabling distinct visual concept synthesis with minimal ov…
An Evaluation of Large Pre-Trained Models for Gesture Recognition using Synthetic Videos
Arun Reddy, Ketul Shah, Corban Rivera +3
In this work, we explore the possibility of using synthetically generated data for video-based gesture recognition with large pre-trained models. We consider whether these models h…
MV2MAE: Multi-View Video Masked Autoencoders
Ketul Shah, Robert Crandall, Jie Xu +4
Videos captured from multiple viewpoints can help in perceiving the 3D structure of the world and benefit computer vision tasks such as action recognition, tracking, etc. In this p…
Unsupervised Video Domain Adaptation with Masked Pre-Training and Collaborative Self-Training
Arun Reddy, William Paul, Corban Rivera +3
In this work, we tackle the problem of unsupervised domain adaptation (UDA) for video action recognition. Our approach, which we call UNITE, uses an image teacher model to adapt a…
DIFFNAT: Improving Diffusion Image Quality Using Natural Image Statistics
Aniket Roy, Maiterya Suin, Anshul Shah +3
Diffusion models have advanced generative AI significantly in terms of editing and creating naturalistic images. However, efficiently improving generated image quality is still of…
HaLP: Hallucinating Latent Positives for Skeleton-based Self-Supervised Learning of Actions
Anshul Shah, Aniket Roy, Ketul Shah +4
Supervised learning of skeleton sequence encoders for action recognition has received significant attention in recent times. However, learning such encoders without labels continue…
Synthetic-to-Real Domain Adaptation for Action Recognition: A Dataset and Baseline Performances
Arun V. Reddy, Ketul Shah, William Paul +6
Human action recognition is a challenging problem, particularly when there is high variability in factors such as subject appearance, backgrounds and viewpoint. While deep neural n…
Cap2Aug: Caption guided Image to Image data Augmentation
Aniket Roy, Anshul Shah, Ketul Shah +2
Visual recognition in a low-data regime is challenging and often prone to overfitting. To mitigate this issue, several data augmentation strategies have been proposed. However, sta…
Improved Modeling of 3D Shapes with Multi-view Depth Maps
Kamal Gupta, Susmija Jabbireddy, Ketul Shah +2
We present a simple yet effective general-purpose framework for modeling 3D shapes by leveraging recent advances in 2D image generation using CNNs. Using just a single depth image…
Photorealistic Image Reconstruction from Hybrid Intensity and Event based Sensor
Prasan A Shedligeri, Kaushik Mitra
Event sensors output a stream of asynchronous brightness changes (called ``events'') at a very high temporal rate. Previous works on recovering the lost intensity information from…