Enhancing UAV object detection with an efficient multi-scale feature MSeg3D: Multi-modal 3D Semantic Segmentation for Autonomous Driving (CVPR2023) EfficientDet: Scalable and Efficient Object Detection
CRGF-YOLO: An Optimized Multi-Scale Feature Fusion Model AI-Powered People Counting System: Optimizing Traffic Control and Safety Management
ACM Transactions on Graphics, 2015 Yizhong Zhang, Weiwei Xu, Yiying Tong, Kun Zhou We propose a real-time approach for BEVSegFormer: Bird's Eye View Semantic Segmentation From Arbitrary Camera Rigs
Robust Real-time 3D Person Detection for Indoor and Outdoor Applications Sponsored by Evolution AI: Papers:
Recursive Hybrid Fusion Pyramid Network for Real-Time Small Object Detection on Embedded Devices YOLO-UAV: Object Detection Method of Unmanned Aerial Vehicle Imagery Based on Efficient Multi-Scale Feature Fusion. Abstract: As Unmanned Aerial
Human skeleton-based action recognition offers a valuable means to understand the intricacies of human behavior because it can In this session, we present methods for lifting object-based representations from sensor data, including FRODO, ODAM, and
This project presents an object classification method for vision and light detection and ranging (LIDAR) fusion of autonomous Authors: Peng, Lang; Chen, Zhirong; fu, zhangjie; Liang, Pengpeng; Cheng, Erkang* Description: Semantic segmentation in bird's
(CVPR2022) InfoGCN: Representation Learning for Human Skeleton-based Action Recognition Vehicle detection on roads based on Yolov5 with multi-scale feature ICPR 2020 - Encoder-Decoder Based CNNs with Multi-Scale-Aware Modules for Crowd Counting
Results of Knowledge-driven and context adapting approach for 3D object detection in point clouds Deep Learning wildfire image fusion and segmentation
[CVPR2023] MOTRv2: Bootstrapping End-to-End Multi-Object Tracking by Pretrained Object Detectors Traffic Light Detection & Recognition in Self Driving Cars || YOLO V3 || Project by Shaik Kashif ||
Vehicle re-ID: past, present and future - Wu Liu ACM Multimedia 2020 Tutorial on Effective and Efficient: Toward Open-world Swin-Transformer-Based YOLOv5 for Small-Object Detection in Remote Sensing Images | RTCL.TV The model achieves an optimal trade-off between detection accuracy, computational cost, and efficiency, making it highly suitable for steel
If you have any copyright issues on video, please send us an email at khawar512@gmail.com. 圖解一階段物件偵測算法_Part04 : FPN Enhancing marine target detection with multi-scale feature fusion in
FPN提出了一個網路架構能結合不同尺度的特徵去偵測更小的物件#FPN. This paper proposes the CRGF-YOLO (Contextual Reparameterized Generalized Feature) model based on YOLOv5. Our approach introduces two innovative modules: the Scale Sequence Feature Fusion Module (SSFF) and the Multi-Scale Feature Extraction Module (MSFE), which
To address these limitations, this paper proposes SRD-YOLOv5, a multi-scale feature fusion framework that enhances the lightweight YOLOv5n model Deep CNN With Multi-Scale Rotation Invariance Features
Step into a more efficient future of crowd monitoring with our groundbreaking AI-powered people counting system. Designed to SILA: An Incremental Learning Approach for Pedestrian Trajectory Prediction Online Structure Analysis for Real-time Indoor Scene Reconstruction
EDB-YOLO: An Enhanced Multi-Scale Feature Fusion Model for IEEE paper on "Deep CNN With Multi-Scale Rotation Invariance Features for ship classification" [9] proposed an efficient pyramid structure based on the Transformer for semi-supervised video object segmentation. The designed Scale-Adaptive Fusion Module (
Multimodal Token Fusion for Vision Transformers | CVPR 2022 YOLOv5 can fuse multi-scale features, their Through efficient multi-scale feature fusion and rich feature expression, the multi
MAL-YOLO: a lightweight algorithm for target detection in side-scan In this compelling video, we embark on an enlightening journey through the cutting-edge world of traffic management empowered Authors: Golnaz Habibi, Nikita Jaipuria, Jonathan P. How Description: The prediction of pedestrian motion is challenging,
Paper presentation at ICPR 2020 Paper links 1. 2. To address the challenge of multi-scale feature extraction, YOLOv5 Multi-Scale Feature Fusion. Electronics 2024, 13, 3989. https://doi
In the past years, the number of applications for mobile robot systems within public areas have been increasing. Employing Github: What is EfficientDet and How EfficientDet is different from
Project Aria CVPR 2022 Tutorial: Egocentric Multi-View 3D Object Detection (7 of 11) Fire Detection using Deep Learning Models, Fire and Smoke Recognition using Deep Learning, Fire Detection using Machine Paper: Code: Abstract: What constitutes an object? This has been a
EfficientDet is an efficient object detection model that achieves a very high mAP at a fraction of the compute requirements of other Title: - Optimize a world-detection system within an autonomous vehicle
Authors: Mingxing Tan, Ruoming Pang, Quoc V. Le Description: Model efficiency has become increasingly important in computer Fire Detection using Deep Learning Models Deep Learning for visible-infrared image fusion and semantic segmentation of wildfire imagery Autor: Jorge Francisco Ciprián
Object Detection & Classification Using CNN-Based Fusion of Vision and LIDAR VR 2022 Presentation - 360 Depth Estimation in the Wild The Depth360 Dataset and the SegFuse Network
Natural action recognition using invariant 3D motion encoding Enhancing UAV object detection with an efficient multi-scale feature fusion framework Experimental results demonstrate that SRD-YOLOv5 ACM Multimedia 2020 Tutorial-part2-Vehicle re-ID: past, present and future - Wu Liu
An Efficient UAV Image Object Detection Algorithm Based on Global We propose MOTRv2, a simple yet effective pipeline to bootstrap end-to-end multi-object tracking with a pretrained object detector Keywords ### #SwinTransformer #YOLOv5 #multiscalefeaturefusion #attentionmechanism #smallobjectdetection
Fire Detection using Python CVPR-2023 paper: Understanding the Robustness of 3D Object Detection with Bird's-Eye-View Representations in Autonomous
Presentation: 360 Depth Estimation in the Wild - The Depth360 Dataset and the SegFuse Network More information: Abstract: We investigate the recognition of actions "in the wild" using 3D motion information. The lack of control over (and CVPR2023 Understanding the Robustness of 3D Object Detection with Bird's Eye View Representations
3D Object Detection & Recognition in Self Driving Cars || Point Pillar || Project by Shaik Kashif || Object Detection for Autonomous Vehicles | 3D object detection | Classification and Tracking
MTD-YOLOv5: Enhancing marine target detection with multi-scale feature fusion in YOLOv5 model effective target feature extraction from Ting Chen | Pix2Seq: A New Language Interface for Object Detection and Beyond Session Tag: THU-PM-104 Abstract: LiDAR and camera are two modalities available for 3D semantic segmentation in
Authors: Ping-Yang Chen, Jun-Wei Hsieh, Chien-Yao Wang, Hong-Yuan Mark Liao Description: This paper proposes a novel Demonstration presented at the 6th International Workshop LowCost 3D - Sensors, Algorithms, Applications at INSA Strasbourg, All the Credits for this Video Belong to Mr. Shaik Baleeghuddin Kashif (B. Tech - Electronics & Communication Engineering)
Visualizing Urban Flow: The Camera-Powered Smart Traffic Management System Fire Detection using Python, Fire Detection using Deep Learning, Fire Detection using Machine Learning, How to detect fire in
EfficientDet Implementation | Object Detection YOLO-UAV: Object Detection Method of Unmanned Aerial Vehicle Class-agnostic Object Detection with Multi-modal Transformer