16 citations · 65 across the 12 of their papers we have counts for
13 papers
GoRela: Go Relative for Viewpoint-Invariant Motion Forecasting
Alexander Cui, Sergio Casas, Kelvin Wong +2
The task of motion forecasting is critical for self-driving vehicles (SDVs) to be able to plan a safe maneuver. Towards this goal, modern approaches reason about the map, the agent…
Asymmetry Disentanglement Network for Interpretable Acute Ischemic Stroke Infarct Segmentation in Non-Contrast CT Scans
Haomiao Ni, Yuan Xue, Kelvin Wong +4
Accurate infarct segmentation in non-contrast CT (NCCT) images is a crucial step toward computer-aided acute ischemic stroke (AIS) assessment. In clinical practice, bilateral symme…
Patcher: Patch Transformers with Mixture of Experts for Precise Medical Image Segmentation
Yanglan Ou, Ye Yuan, Xiaolei Huang +4
We present a new encoder-decoder Vision Transformer architecture, Patcher, for medical image segmentation. Unlike standard Vision Transformers, it employs Patcher blocks that segme…
DeepStroke: An Efficient Stroke Screening Framework for Emergency Rooms with Multimodal Adversarial Deep Learning
Tongan Cai, Haomiao Ni, Mingli Yu +5
In an emergency room (ER) setting, stroke triage or screening is a common challenge. A quick CT is usually done instead of MRI due to MRI's slow throughput and high cost. Clinical…
Non-parametric Memory for Spatio-Temporal Segmentation of Construction Zones for Self-Driving
Min Bai, Shenlong Wang, Kelvin Wong +2
In this paper, we introduce a non-parametric memory representation for spatio-temporal segmentation that captures the local space and time around an autonomous vehicle (AV). Our re…
SceneGen: Learning to Generate Realistic Traffic Scenes
Shuhan Tan, Kelvin Wong, Shenlong Wang +3
We consider the problem of generating realistic traffic scenes automatically. Existing methods typically insert actors into the scene according to a set of hand-crafted heuristics…
MuSCLE: Multi Sweep Compression of LiDAR using Deep Entropy Models
Sourav Biswas, Jerry Liu, Kelvin Wong +2
We present a novel compression algorithm for reducing the storage of LiDAR sensor data streams. Our model exploits spatio-temporal relationships across multiple LiDAR sweeps to red…
Testing the Safety of Self-driving Vehicles by Simulating Perception and Prediction
Kelvin Wong, Qiang Zhang, Ming Liang +4
We present a novel method for testing the safety of self-driving vehicles in simulation. We propose an alternative to sensor simulation, as sensor simulation is expensive and has l…
LiDARsim: Realistic LiDAR Simulation by Leveraging the Real World
Sivabalan Manivasagam, Shenlong Wang, Kelvin Wong +6
We tackle the problem of producing realistic simulations of LiDAR point clouds, the sensor of preference for most self-driving vehicles. We argue that, by leveraging real data, we…
OctSqueeze: Octree-Structured Entropy Model for LiDAR Compression
Lila Huang, Shenlong Wang, Kelvin Wong +2
We present a novel deep compression algorithm to reduce the memory footprint of LiDAR point clouds. Our method exploits the sparsity and structural redundancy between points to red…
Simultaneous Visibility Representations of Undirected Pairs of Graphs
Ben Chugg, William S. Evans, Kelvin Wong
We consider the problem of determining if a pair of undirected graphs , which share the same vertex set, has a representation using opaq…
Identifying Unknown Instances for Autonomous Driving
Kelvin Wong, Shenlong Wang, Mengye Ren +2
In the past few years, we have seen great progress in perception algorithms, particular through the use of deep learning. However, most existing approaches focus on a few categorie…
Deformable Filter Convolution for Point Cloud Reasoning
Yuwen Xiong, Mengye Ren, Renjie Liao +2
Point clouds are the native output of many real-world 3D sensors. To borrow the success of 2D convolutional network architectures, a majority of popular 3D perception models voxeli…