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Found 10 papers, 3 papers with code
Event-based Camera Tracker by $\nabla$t NeRF
To enable the computation of the temporal gradient of the scene, we augment NeRF's camera pose as a time function.
Toward Unsupervised 3D Point Cloud Anomaly Detection using Variational Autoencoder
We propose a deep variational autoencoder-based unsupervised anomaly detection network adapted to the 3D point cloud and an anomaly score specifically for 3D point clouds.
Tangentially Elongated Gaussian Belief Propagation for Event-Based Incremental Optical Flow Estimation
An existing method using local plane fitting of events could utilize the sparsity to realize incremental updates for low-latency estimation; however, its output is merely a normal component of the full optical flow.
Implicit Neural Representations for Variable Length Human Motion Generation
We confirm that our method with a Transformer decoder outperforms all relevant methods on HumanAct12, NTU-RGBD, and UESTC datasets in terms of realism and diversity of generated motions.
Neural Implicit Event Generator for Motion Tracking
Our framework use pre-trained event generation MLP named implicit event generator (IEG) and does motion tracking by updating its state (position and velocity) based on the difference between the observed event and generated event from the current state estimate.
Irregularly Tabulated MLP for Fast Point Feature Embedding
Aiming at drastic speedup for point-feature embeddings at test time, we propose a new framework that uses a pair of multi-layer perceptrons (MLP) and a lookup table (LUT) to transform point-coordinate inputs into high-dimensional features.
Rethinking PointNet Embedding for Faster and Compact Model
PointNet, which is the widely used point-wise embedding method and known as a universal approximator for continuous set functions, can process one million points per second.
CorsNet: 3D Point Cloud Registration by Deep Neural Network
For comparison, we also developed a novel deep learning approach (DirectNet) that directly regresses the pose between point clouds.
Tabulated MLP for Fast Point Feature Embedding
Aiming at a drastic speedup for point-data embeddings at test time, we propose a new framework that uses a pair of multi-layer perceptron (MLP) and look-up table (LUT) to transform point-coordinate inputs into high-dimensional features.
EventNet: Asynchronous Recursive Event Processing
Event cameras are bio-inspired vision sensors that mimic retinas to asynchronously report per-pixel intensity changes rather than outputting an actual intensity image at regular intervals.
