Towards deep radar perception for autonomous driving: Datasets, methods, and challenges
With recent developments, the performance of automotive radar has improved significantly.
The next generation of 4D radar can achieve imaging capability in the form of high …
The next generation of 4D radar can achieve imaging capability in the form of high …
Radars for autonomous driving: A review of deep learning methods and challenges
A Srivastav, S Mandal - IEEE Access, 2023 - ieeexplore.ieee.org
Radar is a key component of the suite of perception sensors used for safe and reliable
navigation of autonomous vehicles. Its unique capabilities include high-resolution velocity …
navigation of autonomous vehicles. Its unique capabilities include high-resolution velocity …
Fiery: Future instance prediction in bird's-eye view from surround monocular cameras
Driving requires interacting with road agents and predicting their future behaviour in order to
navigate safely. We present FIERY: a probabilistic future prediction model in bird's-eye view …
navigate safely. We present FIERY: a probabilistic future prediction model in bird's-eye view …
Standing between past and future: Spatio-temporal modeling for multi-camera 3d multi-object tracking
This work proposes an end-to-end multi-camera 3D multi-object tracking (MOT) framework. It
emphasizes spatio-temporal continuity and integrates both past and future reasoning for …
emphasizes spatio-temporal continuity and integrates both past and future reasoning for …
Robust multimodal vehicle detection in foggy weather using complementary lidar and radar signals
Vehicle detection with visual sensors like lidar and camera is one of the critical functions
enabling autonomous driving. While they generate fine-grained point clouds or high …
enabling autonomous driving. While they generate fine-grained point clouds or high …
Millimeter wave fmcw radars for perception, recognition and localization in automotive applications: A survey
MmWave (millimeter wave) Frequency Modulated Continuous Waves (FMCW) RADARs are
sensors based on frequency-modulated electromagnetic which see their environment in 3D …
sensors based on frequency-modulated electromagnetic which see their environment in 3D …
Stepwise goal-driven networks for trajectory prediction
We propose to predict the future trajectories of observed agents (eg, pedestrians or vehicles)
by estimating and using their goals at multiple time scales. We argue that the goal of a …
by estimating and using their goals at multiple time scales. We argue that the goal of a …
A progressive review: Emerging technologies for ADAS driven solutions
J Nidamanuri, C Nibhanupudi, R Assfalg… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Over the last decade, the Advanced Driver Assistance System (ADAS) concept has evolved
significantly. ADAS involves several technologies such as automotive electronics, vehicle-to …
significantly. ADAS involves several technologies such as automotive electronics, vehicle-to …
TBP-Former: Learning Temporal Bird's-Eye-View Pyramid for Joint Perception and Prediction in Vision-Centric Autonomous Driving
Vision-centric joint perception and prediction (PnP) has become an emerging trend in
autonomous driving research. It predicts the future states of the traffic participants in the …
autonomous driving research. It predicts the future states of the traffic participants in the …
Cramnet: Camera-radar fusion with ray-constrained cross-attention for robust 3d object detection
Robust 3D object detection is critical for safe autonomous driving. Camera and radar
sensors are synergistic as they capture complementary information and work well under …
sensors are synergistic as they capture complementary information and work well under …