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Found 5 papers, 1 papers with code
URS-NeRF: Unordered Rolling Shutter Bundle Adjustment for Neural Radiance Fields
We propose a novel rolling shutter bundle adjustment method for neural radiance fields (NeRF), which utilizes the unordered rolling shutter (RS) images to obtain the implicit 3D representation.
Incremental Neural Implicit Representation with Uncertainty-Filtered Knowledge Distillation
In view of this, we explore the task of incremental learning for NIRs in this work.
Learning Part Segmentation through Unsupervised Domain Adaptation from Synthetic Vehicles
We believe our dataset provides a rich testbed to study UDA for part segmentation and will help to significantly push forward research in this area.
Unsupervised Part Discovery via Feature Alignment
Specifically, given a training image, we find a set of similar images that show instances of the same object category in the same pose, through an affine alignment of their corresponding feature maps.
Modified QPSK Partition Algorithm Based on MAP Estimation for Probabilistically-Shaped 16-QAM
In addition, the filter weight is optimized for different decision thresholds to enhance the tolerance of ASE-induced phase noise.
