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Found 8 papers, 3 papers with code
Project Aria: A New Tool for Egocentric Multi-Modal AI Research
Egocentric, multi-modal data as available on future augmented reality (AR) devices provides unique challenges and opportunities for machine perception.
ERF: Explicit Radiance Field Reconstruction From Scratch
Robustly reconstructing such a volumetric scene model with millions of unknown variables from registered scene images only is a highly non-convex and complex optimization problem.
Neural 3D Video Synthesis from Multi-view Video
We propose a novel approach for 3D video synthesis that is able to represent multi-view video recordings of a dynamic real-world scene in a compact, yet expressive representation that enables high-quality view synthesis and motion interpolation.
LR-CNN: Local-aware Region CNN for Vehicle Detection in Aerial Imagery
This strengthens the local feature invariance for the resampled features and enables detecting vehicles in an arbitrary orientation.
The Replica Dataset: A Digital Replica of Indoor Spaces
We introduce Replica, a dataset of 18 highly photo-realistic 3D indoor scene reconstructions at room and building scale.
Background Subtraction with Real-time Semantic Segmentation
Our proposed framework consists of two components, a traditional BGS segmenter $\mathcal{B}$ and a real-time semantic segmenter $\mathcal{S}$.
Detail-Preserving Pooling in Deep Networks
This is commonly referred to as pooling, and is applied to reduce the number of parameters, improve invariance to certain distortions, and increase the receptive field size.
Virtual Rephotography: Novel View Prediction Error for 3D Reconstruction
Furthermore, using only geometric accuracy by itself does not allow evaluating systems that either lack a geometric scene representation or utilize coarse proxy geometry.
