3D object detection for autonomous driving: A comprehensive survey
Autonomous driving, in recent years, has been receiving increasing attention for its potential
to relieve drivers' burdens and improve the safety of driving. In modern autonomous driving …
to relieve drivers' burdens and improve the safety of driving. In modern autonomous driving …
[HTML][HTML] Deep learning techniques for vehicle detection and classification from images/videos: A survey
Detecting and classifying vehicles as objects from images and videos is challenging in
appearance-based representation, yet plays a significant role in the substantial real-time …
appearance-based representation, yet plays a significant role in the substantial real-time …
Beverse: Unified perception and prediction in birds-eye-view for vision-centric autonomous driving
In this paper, we present BEVerse, a unified framework for 3D perception and prediction
based on multi-camera systems. Unlike existing studies focusing on the improvement of …
based on multi-camera systems. Unlike existing studies focusing on the improvement of …
Vip3d: End-to-end visual trajectory prediction via 3d agent queries
Perception and prediction are two separate modules in the existing autonomous driving
systems. They interact with each other via hand-picked features such as agent bounding …
systems. They interact with each other via hand-picked features such as agent bounding …
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 …
Does physical adversarial example really matter to autonomous driving? towards system-level effect of adversarial object evasion attack
In autonomous driving (AD), accurate perception is indispensable to achieving safe and
secure driving. Due to its safety-criticality, the security of AD perception has been widely …
secure driving. Due to its safety-criticality, the security of AD perception has been widely …
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 …
MetaScenario: A framework for driving scenario data description, storage and indexing
Autonomous driving related researches require the analysis and usage of massive amounts
of driving scenario data. Compared to raw data collected by sensors, scenario data provide …
of driving scenario data. Compared to raw data collected by sensors, scenario data provide …
DeMT: Deformable mixer transformer for multi-task learning of dense prediction
Convolution neural networks (CNNs) and Transformers have their own advantages and both
have been widely used for dense prediction in multi-task learning (MTL). Most of the current …
have been widely used for dense prediction in multi-task learning (MTL). Most of the current …
Multi-task learning with multi-query transformer for dense prediction
Previous multi-task dense prediction studies developed complex pipelines such as multi-
modal distillations in multiple stages or searching for task relational contexts for each task …
modal distillations in multiple stages or searching for task relational contexts for each task …