Browsing by Issue Date

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  • Transformer augmented multi-resolution hash encoding in diffusion model for 3D point cloud denoising 
    Kumari, Seema; Mishra, Utkarsh; Mandal, Srimanta; Raman, Shanmuganathan (Institute of Electrical and Electronics Engineers, 2025-09-14)
    Denoising 3D point cloud strives to remove noise from noisy data. Existing methods address the problem by estimating point-wise displacement from the point feature or by learning the distribution of noise. In this paper, ...
  • Investigating robustness of unsupervised stylegan image restoration 
    Ali, Akbar; Mastan, Indra Deep; Raman, Shanmuganathan (Institute of Electrical and Electronics Engineers, 2025-09-14)
    Recently, generative priors have shown significant improvement for unsupervised image restoration. This study explores the incorporation of multiple loss functions that capture various perceptual and structural aspects of ...
  • GMOT-Mamba: Mamba-based model prediction for generic multiple object tracking 
    Verma, Shashikant; Sebe, Nicu; Raman, Shanmuganathan (Institute of Electrical and Electronics Engineers, 2025-09-14)
    We introduce GMOT-Mamba, a novel Mamba-based model prediction framework for Generic Multiple Object Tracking (GMOT) in video sequences. Our approach features a Weighted Feature Pooling (WFP) layer, which processes encoded ...
  • Deep unsupervised despeckling with unbiased risk estimation 
    Gupta, Ashutosh; Seelamantula, Chandra Sekhar; Blu, Thierry; Dube, Nitant; Raman, Shanmuganathan (Institute of Electrical and Electronics Engineers, 2025-09-14)
    Despeckling of Synthetic Aperture Radar (SAR) images has seen significant progress in recent years, largely driven by advancements in deep learning techniques. However, many of these approaches face challenges when applied ...
  • Darts: deformable animation ready templates for clothing humans 
    Verma, Shashikant; Raman, Shanmuganathan (Institute of Electrical and Electronics Engineers, 2025-09-14)
    Accurate 3D modeling of humans and high-fidelity garments is crucial in computer vision and graphics, impacting gaming, virtual, and augmented reality applications. While recent data-driven approaches have progressed in ...
  • COT-AD: cotton analysis dataset 
    Ali, Akbar; Vyas, Mahek; Debnath, Soumyaratna; Kamra, Chanda Grover; Khalane, Jaidev Sanjay; Devanesan, Reuben Shibu; Mastan, Indra Deep; Sankaranarayanan, Subramanian; Khanna, Pankaj; Raman, Shanmuganathan (Institute of Electrical and Electronics Engineers, 2025-09-14)
    This paper presents COT-AD, a comprehensive Dataset designed to enhance cotton crop analysis through computer vision. Comprising over 25,000 images captured throughout the cotton growth cycle, with 5,000 annotated images, ...

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