Papers Video Object Detection
“Video Object Detection” 태그가 달린 논문 159편 · 필터 해제
DFA: Dynamic Feature Aggregation for Efficient Video Object Detection
Video object detection is a fundamental yet challenging task in computer vision. One practical solution is to take advantage of temporal information from the video and apply feature aggregation to enhance the object feat…
Objectobject-detectionObject DetectionVideo Object DetectionPTSEFormer: Progressive Temporal-Spatial Enhanced TransFormer Towards Video Object Detection
Recent years have witnessed a trend of applying context frames to boost the performance of object detection as video object detection. Existing methods usually aggregate features at one stroke to enhance the feature. The…
object-detectionObject DetectionVideo Object DetectionDAFA: Diversity-Aware Feature Aggregation for Attention-Based Video Object Detection
We present a framework for attention-based video object detection using a simple yet effective external memory management algorithm. An attention mechanism has been adopted in video object detection task to enrich the fe…
DiversityManagementobject-detectionObject Detection+1TemporalNet: Real-time 2D-3D Video Object Detection
Designing a video detection network based on state-of-the-art single-image object detectors may seem like an obvious choice. However, video object detection has extra challenges due to the lower quality of individual fra…
GPUObjectobject-detectionObject Detection+1YOLOV: Making Still Image Object Detectors Great at Video Object Detection
Video object detection (VID) is challenging because of the high variation of object appearance as well as the diverse deterioration in some frames. On the positive side, the detection in a certain frame of a video, compa…
GPUObjectobject-detectionObject Detection+1Real-Time Robust Video Object Detection System Against Physical-World Adversarial Attacks
DNN-based video object detection (VOD) powers autonomous driving and video surveillance industries with rising importance and promising opportunities. However, adversarial patch attack yields huge concern in live vision …
Adversarial AttackAutonomous DrivingFeature ImportanceObject+3Graph Neural Network and Spatiotemporal Transformer Attention for 3D Video Object Detection from Point Clouds
Previous works for LiDAR-based 3D object detection mainly focus on the single-frame paradigm. In this paper, we propose to detect 3D objects by exploiting temporal information in multiple frames, i.e., the point cloud vi…
3D Object DetectionGraph Neural Networkobject-detectionObject Detection+1QueryProp: Object Query Propagation for High-Performance Video Object Detection
Video object detection has been an important yet challenging topic in computer vision. Traditional methods mainly focus on designing the image-level or box-level feature propagation strategies to exploit temporal informa…
Objectobject-detectionObject DetectionVideo Object Detection+1Exploring Temporally Dynamic Data Augmentation for Video Recognition
Data augmentation has recently emerged as an essential component of modern training recipes for visual recognition tasks. However, data augmentation for video recognition has been rarely explored despite its effectivenes…
Action LocalizationAction SegmentationData AugmentationImage Augmentation+4Video Sparse Transformer With Attention-Guided Memory for Video Object Detection
Detecting objects in a video, known as Video Object Detection (VOD), is challenging since appearance changes of objects over time may bring detection errors. Recent research has focused on aggregating features from adjac…
Objectobject-detectionObject DetectionPosition+2Representation Recycling for Streaming Video Analysis
We present StreamDEQ, a method that aims to infer frame-wise representations on videos with minimal per-frame computation. Conventional deep networks do feature extraction from scratch at each frame in the absence of ad-…
object-detectionObject DetectionPose EstimationSemantic Segmentation+2Single Object Tracking Research: A Survey
Visual object tracking is an important task in computer vision, which has many real-world applications, e.g., video surveillance, visual navigation. Visual object tracking also has many challenges, e.g., object occlusion…
Objectobject-detectionObject DetectionObject Tracking+5SALISA: Saliency-based Input Sampling for Efficient Video Object Detection
High-resolution images are widely adopted for high-performance object detection in videos. However, processing high-resolution inputs comes with high computation costs, and naive down-sampling of the input to reduce the …
Objectobject-detectionObject DetectionVideo Object DetectionDelta Distillation for Efficient Video Processing
This paper aims to accelerate video stream processing, such as object detection and semantic segmentation, by leveraging the temporal redundancies that exist between video frames. Instead of propagating and warping featu…
Knowledge Distillationobject-detectionObject DetectionOptical Flow Estimation+3TransVOD: End-to-End Video Object Detection with Spatial-Temporal Transformers
Detection Transformer (DETR) and Deformable DETR have been proposed to eliminate the need for many hand-designed components in object detection while demonstrating good performance as previous complex hand-crafted detect…
GPUObjectobject-detectionObject Detection+2SmartAdapt: Multi-Branch Object Detection Framework for Videos on Mobiles
Several recent works seek to create lightweight deep networks for video object detection on mobiles. We observe that many existing detectors, previously deemed computationally costly for mobiles, intrinsically suppor…
object-detectionObject DetectionVideo Object DetectionVirtuoso: Video-based Intelligence for real-time tuning on SOCs
Efficient and adaptive computer vision systems have been proposed to make computer vision tasks, such as image classification and object detection, optimized for embedded or mobile devices. These solutions, quite recent …
image-classificationImage Classificationobject-detectionObject Detection+1TYolov5: A Temporal Yolov5 Detector Based on Quasi-Recurrent Neural Networks for Real-Time Handgun Detection in Video
Timely handgun detection is a crucial problem to improve public safety; nevertheless, the effectiveness of many surveillance systems still depends of finite human attention. Much of the previous research on handgun detec…
Data AugmentationImage Augmentationobject-detectionObject Detection+1SiamPolar: Semi-supervised Realtime Video Object Segmentation with Polar Representation
Video object segmentation (VOS) is an essential part of autonomous vehicle navigation. The real-time speed is very important for the autonomous vehicle algorithms along with the accuracy metric. In this paper, we propose…
Objectobject-detectionObject DetectionSemantic Segmentation+3AI Accelerator Survey and Trends
Over the past several years, new machine learning accelerators were being announced and released every month for a variety of applications from speech recognition, video object detection, assisted driving, and many data …
BenchmarkingComputational Efficiencyobject-detectionObject Detection+4