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