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Found 11 papers, 4 papers with code
Neural Collapse Inspired Federated Learning with Non-iid Data
One of the challenges in federated learning is the non-independent and identically distributed (non-iid) characteristics between heterogeneous devices, which cause significant differences in local updates and affect the performance of the central server.
General Rotation Invariance Learning for Point Clouds via Weight-Feature Alignment
Compared to 2D images, 3D point clouds are much more sensitive to rotations.
Learning A Simulation-based Visual Policy for Real-world Peg In Unseen Holes
This paper proposes a learning-based visual peg-in-hole that enables training with several shapes in simulation, and adapting to arbitrary unseen shapes in real world with minimal sim-to-real cost.
Neural Collapse Inspired Attraction-Repulsion-Balanced Loss for Imbalanced Learning
Class imbalance distribution widely exists in real-world engineering.
Sparse Fuse Dense: Towards High Quality 3D Detection with Depth Completion
Many multi-modal methods are proposed to alleviate this issue, while different representations of images and point clouds make it difficult to fuse them, resulting in suboptimal performance.
Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network?
Modern deep neural networks for classification usually jointly learn a backbone for representation and a linear classifier to output the logit of each class.
Ranked #21 on
Long-tail Learning
on CIFAR-10-LT (ρ=100)
X-view: Non-egocentric Multi-View 3D Object Detector
3D object detection algorithms for autonomous driving reason about 3D obstacles either from 3D birds-eye view or perspective view or both.
Boundary-Aware Dense Feature Indicator for Single-Stage 3D Object Detection from Point Clouds
3D object detection based on point clouds has become more and more popular.
SQLFlow: A Bridge between SQL and Machine Learning
Previous database systems extended their SQL dialect to support ML.
PI-RCNN: An Efficient Multi-sensor 3D Object Detector with Point-based Attentive Cont-conv Fusion Module
Moreover, based on the PACF module, we propose a 3D multi-sensor multi-task network called Pointcloud-Image RCNN(PI-RCNN as brief), which handles the image segmentation and 3D object detection tasks.
Exploring Auxiliary Context: Discrete Semantic Transfer Hashing for Scalable Image Retrieval
To address the problem, in this paper, we propose a novel hashing approach, dubbed as \emph{Discrete Semantic Transfer Hashing} (DSTH).
