Abstract: No-reference point cloud quality assessment (NR-PCQA) aims to automatically evaluate the perceptual quality of distorted point clouds without available reference, which have achieved ...

Abstract: Recently, many self-supervised pre-training methods have been proposed to improve the performance of deep neural networks (DNNs) for 3D point clouds processing. However, the common mechanism ...

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Drone Shakti (“Eagle on Arm”) is the Indian Army’s EME-led, indigenous UAS ecosystem for production, repair and field ...

Abstract: Recent intensive and extensive development of the fifth-generation (5G) of cellular networks has led to their deployment throughout much of the world. As part of this implementation, one of ...

Odisha’s Republic Day tableau highlighted the inspiring journey of Sundargarh woman Munni Tigga, a locomotive pilot who ...

Data plays a crucial role in training learning-based methods for 3D point cloud registration. However, the real-world dataset is expensive to build, while rendering-based synthetic data suffers from ...

The Indian Navy has grown significantly over the years and today boasts a formidable fleet of warships, submarines, aircraft, destroyers, frigates and aircraft carriers. INS Vikramaditya and INS ...

UniPre3D is the first unified pre-training method for 3D point clouds that effectively handles both object- and scene-level data through cross-modal Gaussian splatting. Our proposed pre-training task ...

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Abstract: Recent advances in deep neural networks have achieved higher accuracy with more complex models. Nevertheless, they require much longer training time. To reduce the training time, training ...

Abstract: Deploying LiDAR-based detectors on edge devices presents significant challenges due to limited computing power and memory. Post-training quantization (PTQ) requires only a small dataset for ...