Recent advances and perspectives in deep learning techniques for 3D point cloud data processing
In recent years, deep learning techniques for processing 3D point cloud data have seen
significant advancements, given their unique ability to extract relevant features and handle …
significant advancements, given their unique ability to extract relevant features and handle …
Accelerating DETR convergence via semantic-aligned matching
Abstract The recently developed DEtection TRansformer (DETR) establishes a new object
detection paradigm by eliminating a series of hand-crafted components. However, DETR …
detection paradigm by eliminating a series of hand-crafted components. However, DETR …
Cross-modal orthogonal high-rank augmentation for rgb-event transformer-trackers
This paper addresses the problem of cross-modal object tracking from RGB videos and
event data. Rather than constructing a complex cross-modal fusion network, we explore the …
event data. Rather than constructing a complex cross-modal fusion network, we explore the …
Human-centric scene understanding for 3d large-scale scenarios
Human-centric scene understanding is significant for real-world applications, but it is
extremely challenging due to the existence of diverse human poses and actions, complex …
extremely challenging due to the existence of diverse human poses and actions, complex …
Transformers in 3d point clouds: A survey
Transformers have been at the heart of the Natural Language Processing (NLP) and
Computer Vision (CV) revolutions. The significant success in NLP and CV inspired exploring …
Computer Vision (CV) revolutions. The significant success in NLP and CV inspired exploring …
Temporal consistent 3D lidar representation learning for semantic perception in autonomous driving
Semantic perception is a core building block in autonomous driving, since it provides
information about the drivable space and location of other traffic participants. For learning …
information about the drivable space and location of other traffic participants. For learning …
Toward robust 3d perception for autonomous vehicles: A review of adversarial attacks and countermeasures
At present the perception system of autonomous vehicles is grounded on 3D vision
technologies along with deep learning to process depth information. Although deep learning …
technologies along with deep learning to process depth information. Although deep learning …
CXTrack: Improving 3D point cloud tracking with contextual information
Abstract 3D single object tracking plays an essential role in many applications, such as
autonomous driving. It remains a challenging problem due to the large appearance variation …
autonomous driving. It remains a challenging problem due to the large appearance variation …
Glt-t: Global-local transformer voting for 3d single object tracking in point clouds
Current 3D single object tracking methods are typically based on VoteNet, a 3D region
proposal network. Despite the success, using a single seed point feature as the cue for offset …
proposal network. Despite the success, using a single seed point feature as the cue for offset …
MPCT: Multiscale point cloud transformer with a residual network
The self-attention (SA) network revisits the essence of data and has achieved remarkable
results in text processing and image analysis. SA is conceptualized as a set operator that is …
results in text processing and image analysis. SA is conceptualized as a set operator that is …