Search Results for author:
Found 13 papers, 5 papers with code
Waymo Open Dataset: Panoramic Video Panoptic Segmentation
We therefore present the Waymo Open Dataset: Panoramic Video Panoptic Segmentation Dataset, a large-scale dataset that offers high-quality panoptic segmentation labels for autonomous driving.
EV-FlowNet: Self-Supervised Optical Flow Estimation for Event-based Cameras
Event-based cameras have shown great promise in a variety of situations where frame based cameras suffer, such as high speed motions and high dynamic range scenes.
Unsupervised Event-based Learning of Optical Flow, Depth, and Egomotion
In this work, we propose a novel framework for unsupervised learning for event cameras that learns motion information from only the event stream.
Spike-FlowNet: Event-based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks
Spiking Neural Networks (SNNs) serve as ideal paradigms to handle event camera outputs, but deep SNNs suffer in terms of performance due to the spike vanishing phenomenon.
EventGAN: Leveraging Large Scale Image Datasets for Event Cameras
Event cameras provide a number of benefits over traditional cameras, such as the ability to track incredibly fast motions, high dynamic range, and low power consumption.
Realtime Time Synchronized Event-based Stereo
In this work, we propose a novel event based stereo method which addresses the problem of motion blur for a moving event camera.
The Multi Vehicle Stereo Event Camera Dataset: An Event Camera Dataset for 3D Perception
Event based cameras are a new passive sensing modality with a number of benefits over traditional cameras, including extremely low latency, asynchronous data acquisition, high dynamic range and very low power consumption.
Robotics
Robustness Meets Deep Learning: An End-to-End Hybrid Pipeline for Unsupervised Learning of Egomotion
In this work, we propose a method that combines unsupervised deep learning predictions for optical flow and monocular disparity with a model based optimization procedure for instantaneous camera pose.
Event-Based Visual Inertial Odometry
An Extended Kalman Filter with a structureless measurement model then fuses the feature tracks with the output of the IMU.
Motion Equivariant Networks for Event Cameras with the Temporal Normalization Transform
In this work, we propose a novel transformation for events from an event camera that is equivariant to optical flow under convolutions in the 3-D spatiotemporal domain.
Instance Segmentation with Cross-Modal Consistency
We demonstrate that this formulation encourages the models to learn embeddings that are invariant to viewpoint variations and consistent across sensor modalities.
Superpixel Transformers for Efficient Semantic Segmentation
Finally, we directly project the superpixel class predictions back into the pixel space using the associations between the superpixels and the image pixel features.
3D Open-Vocabulary Panoptic Segmentation with 2D-3D Vision-Language Distillation
3D panoptic segmentation is a challenging perception task, especially in autonomous driving.
