1 citations · 1 across the 7 of their papers we have counts for
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Stabilizing Camera-Controlled Novel View Synthesis at Inference Time
Prajwal Singh, Arjun Badola, Seema Kumari +2
Training-free, camera-controlled novel view synthesis from a single image using pre-trained video diffusion models often becomes unstable under large camera motion and long generat…
BloomCoreset: Fast Coreset Sampling using Bloom Filters for Fine-Grained Self-Supervised Learning
Prajwal Singh, Gautam Vashishtha, Indra Deep Mastan +1
The success of deep learning in supervised fine-grained recognition for domain-specific tasks relies heavily on expert annotations. The Open-Set for fine-grained Self-Supervised Le…
Incremental Multi-Scene Modeling via Continual Neural Graphics Primitives
Prajwal Singh, Ashish Tiwari, Gautam Vashishtha +1
Neural radiance fields (NeRF) have revolutionized photorealistic rendering of novel views for 3D scenes. Despite their growing popularity and efficiency as 3D resources, NeRFs face…
Learning Robust Deep Visual Representations from EEG Brain Recordings
Prajwal Singh, Dwip Dalal, Gautam Vashishtha +2
Decoding the human brain has been a hallmark of neuroscientists and Artificial Intelligence researchers alike. Reconstruction of visual images from brain Electroencephalography (EE…
Single Image LDR to HDR Conversion using Conditional Diffusion
Dwip Dalal, Gautam Vashishtha, Prajwal Singh +1
Digital imaging aims to replicate realistic scenes, but Low Dynamic Range (LDR) cameras cannot represent the wide dynamic range of real scenes, resulting in under-/overexposed imag…
A Graph Neural Network Approach for Temporal Mesh Blending and Correspondence
Aalok Gangopadhyay, Abhinav Narayan Harish, Prajwal Singh +1
We have proposed a self-supervised deep learning framework for solving the mesh blending problem in scenarios where the meshes are not in correspondence. To solve this problem, we…