6 papers · 1 filter
Image-Text Knowledge Modeling for Unsupervised Multi-Scenario Person Re-Identification
Zhiqi Pang, Lingling Zhao, Yang Liu +2
We propose unsupervised multi-scenario (UMS) person re-identification (ReID) as a new task that expands ReID across diverse scenarios (cross-resolution, clothing change, etc.) with…
Foundry: Distilling 3D Foundation Models for the Edge
Guillaume Letellier, Siddharth Srivastava, Frédéric Jurie +1
Foundation models pre-trained with self-supervised learning (SSL) on large-scale datasets have become powerful general-purpose feature extractors. However, their immense size and c…
Styleclone: Face Stylization with Diffusion Based Data Augmentation
Neeraj Matiyali, Siddharth Srivastava, Gaurav Sharma
We present StyleClone, a method for training image-to-image translation networks to stylize faces in a specific style, even with limited style images. Our approach leverages textua…
Preserve Anything: Controllable Image Synthesis with Object Preservation
Prasen Kumar Sharma, Neeraj Matiyali, Siddharth Srivastava +1
We introduce \textit{Preserve Anything}, a novel method for controlled image synthesis that addresses key limitations in object preservation and semantic consistency in text-to-ima…
OmniVec2 -- A Novel Transformer based Network for Large Scale Multimodal and Multitask Learning
Siddharth Srivastava, Gaurav Sharma
We present a novel multimodal multitask network and associated training algorithm. The method is capable of ingesting data from approximately 12 different modalities namely image,…
OmniVec: Learning robust representations with cross modal sharing
Siddharth Srivastava, Gaurav Sharma
Majority of research in learning based methods has been towards designing and training networks for specific tasks. However, many of the learning based tasks, across modalities, sh…