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Found 17 papers, 7 papers with code
Maximum Likelihood CFO Estimation for High-Mobility OFDM Systems: A Chinese Remainder Theorem Based Method
Orthogonal frequency division multiplexing (OFDM) is a widely adopted wireless communication technique but is sensitive to the carrier frequency offset (CFO).
Towards 3D Object Detection with 2D Supervision
We propose a temporal 2D transformation to bridge the 3D predictions with temporal 2D labels.
Implicit and Efficient Point Cloud Completion for 3D Single Object Tracking
The point cloud based 3D single object tracking has drawn increasing attention.
Quality Matters: Embracing Quality Clues for Robust 3D Multi-Object Tracking
Recent advanced works generally employ a series of object attributes, e. g., position, size, velocity, and appearance, to provide the clues for the association in 3D MOT.
DBQ-SSD: Dynamic Ball Query for Efficient 3D Object Detection
Many point-based 3D detectors adopt point-feature sampling strategies to drop some points for efficient inference.
StreamYOLO: Real-time Object Detection for Streaming Perception
In this paper, we explore the performance of real time models on this metric and endow the models with the capacity of predicting the future, significantly improving the results for streaming perception.
A Semantic Consistency Feature Alignment Object Detection Model Based on Mixed-Class Distribution Metrics
Then, a Semantic Consistency Feature Alignment Model (SCFAM) based on mixed-classes $H-divergence$ was also presented.
Real-time Object Detection for Streaming Perception
In this paper, instead of searching trade-offs between accuracy and speed like previous works, we point out that endowing real-time models with the ability to predict the future is the key to dealing with this problem.
Ranked #1 on
Real-Time Object Detection
on Argoverse-HD (Full-Stack, Val)
(sAP metric, using extra
training data)
Feature Selection With Maximal Relevance and Minimal Supervised Redundancy
Based on conditional mutual information and entropy, a new supervised similarity measure is proposed.
Data Heterogeneity-Robust Federated Learning via Group Client Selection in Industrial IoT
In this paper, we propose FedGS, which is a hierarchical cloud-edge-end FL framework for 5G empowered industries, to improve industrial FL performance on non-i. i. d.
Performance assessment and tuning of PID control using TLBO: the single-loop case and PI/P cascade case
Minimum output variance (MOV) is used as a benchmark for CPA of PID, but it is difficult to be found due to the associated non-convex optimization problem.
Gaussian Guided IoU: A Better Metric for Balanced Learning on Object Detection
This results in two problems: (1) only one anchor is assigned to most of the slender objects which leads to insufficient supervision information for the slender objects during training and the performance on the slender objects is hurt; (2) IoU can not accurately represent the alignment degree between the receptive field of the feature at the anchor's center and the object.
Carton dataset synthesis method for domain shift based on foreground texture decoupling and replacement
To solve this problem, a novel image synthesis method is proposed to replace the foreground texture of the source datasets with the texture of the target datasets.
SCD: A Stacked Carton Dataset for Detection and Segmentation
In this paper, we present a large-scale carton dataset named Stacked Carton Dataset(SCD) with the goal of advancing the state-of-the-art in carton detection.
IoU-aware Single-stage Object Detector for Accurate Localization
The detection confidence is then used as the input of the subsequent NMS and COCO AP computation, which will substantially improve the localization accuracy of models.
IoU-balanced Loss Functions for Single-stage Object Detection
The IoU-balanced localization loss decreases the gradient of examples with low IoU and increases the gradient of examples with high IoU, which can improve the localization accuracy of models.
A Novel Demodulation and Estimation Algorithm for Blackout Communication: Extract Principal Components with Deep Learning
For reentry or near space communication, owing to the influence of the time-varying plasma sheath channel environment, the received IQ baseband signals are severely rotated on the constellation.
