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Know-Your-Scene (KYS)-SLAM: Hierarchical Semantic-Motion Priors for Feature Matching in Stereo Visual SLAM
Preeti Chatterjee, Jin Lu, Jin Sun +1
Stereo visual SLAM systems built on local descriptors suffer from semantic ambiguity, instance-level confusion, and independently moving objects, each corrupting data association a…
Fast and Generalizable NeRF Architecture Selection for Satellite Scene Reconstruction
Devjyoti Chakraborty, Zaki Sukma, Rakandhiya D. Rachmanto +6
Neural Radiance Fields (NeRF) have emerged as a powerful approach for photorealistic 3D reconstruction from multi-view images. However, deploying NeRF for satellite imagery remains…
-NeRF: Incremental Refinement of Neural Radiance Fields through Residual Control and Knowledge Transfer
Kriti Ghosh, Devjyoti Chakraborty, Lakshmish Ramaswamy +4
Neural Radiance Fields (NeRFs) have demonstrated remarkable capabilities in 3D reconstruction and novel view synthesis. However, most existing NeRF frameworks require complete retr…
F4D: Factorized 4D Convolutional Neural Network for Efficient Video-level Representation Learning
Mohammad Al-Saad, Lakshmish Ramaswamy, Suchendra Bhandarkar
Recent studies have shown that video-level representation learning is crucial to the capture and understanding of the long-range temporal structure for video action recognition. Mo…
Matching Disparate Image Pairs Using Shape-Aware ConvNets
Shefali Srivastava, Abhimanyu Chopra, Arun CS Kumar +2
An end-to-end trainable ConvNet architecture, that learns to harness the power of shape representation for matching disparate image pairs, is proposed. Disparate image pairs are de…
Deep Spectral Correspondence for Matching Disparate Image Pairs
Arun CS Kumar, Shefali Srivastava, Anirban Mukhopadhyay +1
A novel, non-learning-based, saliency-aware, shape-cognizant correspondence determination technique is proposed for matching image pairs that are significantly disparate in nature.…