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Found 8 papers, 2 papers with code
Clusterformer: Cluster-based Transformer for 3D Object Detection in Point Clouds
Attributed to the unstructured and sparse nature of point clouds, the transformer shows greater potential in point clouds data processing.
Towards Comprehensive Representation Enhancement in Semantics-guided Self-supervised Monocular Depth Estimation
Semantics-guided self-supervised monocular depth estimation has been widely researched, owing to the strong cross-task correlation of depth and semantics.
Benign Adversarial Attack: Tricking Models for Goodness
In spite of the successful application in many fields, machine learning models today suffer from notorious problems like vulnerability to adversarial examples.
RangeIoUDet: Range Image Based Real-Time 3D Object Detector Optimized by Intersection Over Union
Benefiting from the dense representation of the range image, RangeIoUDet is entirely constructed based on 2D convolution, making it possible to have a fast inference speed.
An Experimental Study of Semantic Continuity for Deep Learning Models
Deep learning models suffer from the problem of semantic discontinuity: small perturbations in the input space tend to cause semantic-level interference to the model output.
MAFF-Net: Filter False Positive for 3D Vehicle Detection with Multi-modal Adaptive Feature Fusion
Experimental results on the KITTI dataset demonstrate significant improvement in filtering false positive over the approach using only point cloud data.
RangeRCNN: Towards Fast and Accurate 3D Object Detection with Range Image Representation
We present RangeRCNN, a novel and effective 3D object detection framework based on the range image representation.
Adversarial Privacy-preserving Filter
While widely adopted in practical applications, face recognition has been critically discussed regarding the malicious use of face images and the potential privacy problems, e. g., deceiving payment system and causing personal sabotage.
