1 citations · 1 across the 8 of their papers we have counts for
9 papers
DesignSense: A Human Preference Dataset and Reward Modeling Framework for Graphic Layout Generation
Varun Gopal, Rishabh Jain, Aradhya Mathur +6
Graphic layouts serve as an important and engaging medium for visual communication across different channels. While recent layout generation models have demonstrated impressive cap…
AFRAgent : An Adaptive Feature Renormalization Based High Resolution Aware GUI agent
Neeraj Anand, Rishabh Jain, Sohan Patnaik +2
There is a growing demand for mobile user interface (UI) automation, driven by its broad applications across industries. With the advent of visual language models (VLMs), GUI autom…
HIRE: Lightweight High-Resolution Image Feature Enrichment for Multimodal LLMs
Nikitha SR, Aradhya Neeraj Mathur, Tarun Ram Menta +2
The integration of high-resolution image features in modern multimodal large language models has demonstrated significant improvements in fine-grained visual understanding tasks, a…
EOPose : Exemplar-based object reposing using Generalized Pose Correspondences
Sarthak Mehrotra, Rishabh Jain, Mayur Hemani +2
Reposing objects in images has a myriad of applications, especially for e-commerce where several variants of product images need to be produced quickly. In this work, we leverage t…
AesthetiQ: Enhancing Graphic Layout Design via Aesthetic-Aware Preference Alignment of Multi-modal Large Language Models
Sohan Patnaik, Rishabh Jain, Balaji Krishnamurthy +1
Visual layouts are essential in graphic design fields such as advertising, posters, and web interfaces. The application of generative models for content-aware layout generation has…
DoPTA: Improving Document Layout Analysis using Patch-Text Alignment
Nikitha SR, Tarun Ram Menta, Mausoom Sarkar
The advent of multimodal learning has brought a significant improvement in document AI. Documents are now treated as multimodal entities, incorporating both textual and visual info…
LOCATE: Self-supervised Object Discovery via Flow-guided Graph-cut and Bootstrapped Self-training
Silky Singh, Shripad Deshmukh, Mausoom Sarkar +1
Learning object segmentation in image and video datasets without human supervision is a challenging problem. Humans easily identify moving salient objects in videos using the gesta…
UMFuse: Unified Multi View Fusion for Human Editing applications
Rishabh Jain, Mayur Hemani, Duygu Ceylan +4
Numerous pose-guided human editing methods have been explored by the vision community due to their extensive practical applications. However, most of these methods still use an ima…
VGFlow: Visibility guided Flow Network for Human Reposing
Rishabh Jain, Krishna Kumar Singh, Mayur Hemani +4
The task of human reposing involves generating a realistic image of a person standing in an arbitrary conceivable pose. There are multiple difficulties in generating perceptually a…