activity
20212026
most citedSSL-Lanes: Self-Supervised Learning for Motion Forecasting in Autonomous Driving

12 citations · 22 across the 13 of their papers we have counts for

collaborators

14 papers

cs.CV2026

Spatial4D-Bench: A Versatile 4D Spatial Intelligence Benchmark

Pan Wang, Yang Liu, Guile Wu +23

4D spatial intelligence involves perceiving and processing how objects move or change over time. Humans naturally possess 4D spatial intelligence, supporting a broad spectrum of sp…

cs.CV2025

DCDB: Dynamic Conditional Dual Diffusion Bridge for Ill-posed Multi-Tasks

Chengjie Huang, Jiafeng Yan, Jing Li +1

Conditional diffusion models have made impressive progress in the field of image processing, but the characteristics of constructing data distribution pathways make it difficult to…

cs.HC2025

MindChat: Enhancing BCI Spelling with Large Language Models in Realistic Scenarios

JIaheng Wang, Yucun Zhong, Chengjie Huang +1

Brain-computer interface (BCI) spellers can render a new communication channel independent of peripheral nervous system, which are especially valuable for patients with severe moto…

cs.CV2025

How Hard Is Snow? A Paired Domain Adaptation Dataset for Clear and Snowy Weather: CADC+

Mei Qi Tang, Sean Sedwards, Chengjie Huang +1

The impact of snowfall on 3D object detection performance remains underexplored. Conducting such an evaluation requires a dataset with sufficient labelled data from both weather co…

cs.CV2025

MFSeg: Efficient Multi-frame 3D Semantic Segmentation

Chengjie Huang, Krzysztof Czarnecki

We propose MFSeg, an efficient multi-frame 3D semantic segmentation framework. By aggregating point cloud sequences at the feature level and regularizing the feature extraction and…

cs.CV2024

VADet: Multi-frame LiDAR 3D Object Detection using Variable Aggregation

Chengjie Huang, Vahdat Abdelzad, Sean Sedwards +1

Input aggregation is a simple technique used by state-of-the-art LiDAR 3D object detectors to improve detection. However, increasing aggregation is known to have diminishing return…

cs.CV2024

SOAP: Cross-sensor Domain Adaptation for 3D Object Detection Using Stationary Object Aggregation Pseudo-labelling

Chengjie Huang, Vahdat Abdelzad, Sean Sedwards +1

We consider the problem of cross-sensor domain adaptation in the context of LiDAR-based 3D object detection and propose Stationary Object Aggregation Pseudo-labelling (SOAP) to gen…

cs.CV2024★ 1 cited

SSL-Interactions: Pretext Tasks for Interactive Trajectory Prediction

Prarthana Bhattacharyya, Chengjie Huang, Krzysztof Czarnecki

This paper addresses motion forecasting in multi-agent environments, pivotal for ensuring safety of autonomous vehicles. Traditional as well as recent data-driven marginal trajecto…

cs.CV2023

Object Re-Identification from Point Clouds

Benjamin Thérien, Chengjie Huang, Adrian Chow +1

Object re-identification (ReID) from images plays a critical role in application domains of image retrieval (surveillance, retail analytics, etc.) and multi-object tracking (autono…

cs.CV2022

Out-of-Distribution Detection for LiDAR-based 3D Object Detection

Chengjie Huang, Van Duong Nguyen, Vahdat Abdelzad +5

3D object detection is an essential part of automated driving, and deep neural networks (DNNs) have achieved state-of-the-art performance for this task. However, deep models are no…

cs.CV2022★ 12 cited

SSL-Lanes: Self-Supervised Learning for Motion Forecasting in Autonomous Driving

Prarthana Bhattacharyya, Chengjie Huang, Krzysztof Czarnecki

Self-supervised learning (SSL) is an emerging technique that has been successfully employed to train convolutional neural networks (CNNs) and graph neural networks (GNNs) for more…

cs.CV2022★ 9 cited

LiDAR-MIMO: Efficient Uncertainty Estimation for LiDAR-based 3D Object Detection

Matthew Pitropov, Chengjie Huang, Vahdat Abdelzad +2

The estimation of uncertainty in robotic vision, such as 3D object detection, is an essential component in developing safe autonomous systems aware of their own performance. Howeve…

cs.LG2021

The missing link: Developing a safety case for perception components in automated driving

Rick Salay, Krzysztof Czarnecki, Hiroshi Kuwajima +6

Safety assurance is a central concern for the development and societal acceptance of automated driving (AD) systems. Perception is a key aspect of AD that relies heavily on Machine…

cs.CV2021

SA-Det3D: Self-Attention Based Context-Aware 3D Object Detection

Prarthana Bhattacharyya, Chengjie Huang, Krzysztof Czarnecki

Existing point-cloud based 3D object detectors use convolution-like operators to process information in a local neighbourhood with fixed-weight kernels and aggregate global context…