Papers Video Object Detection
“Video Object Detection” 태그가 달린 논문 159편 · 필터 해제
ApproxDet: Content and Contention-Aware Approximate Object Detection for Mobiles
Advanced video analytic systems, including scene classification and object detection, have seen widespread success in various domains such as smart cities and autonomous transportation. With an ever-growing number of pow…
Objectobject-detectionObject DetectionObject Tracking+3Robust and Efficient Post-Processing for Video Object Detection (REPP)
Object recognition in video is an important task for plenty of applications, including autonomous driving perception, surveillance tasks, wearable devices or IoT networks. Object recognition using video data is more chal…
Autonomous DrivingDense Object DetectionObjectobject-detection+4Robust and efficient post-processing for video object detection
Object recognition in video is an important task for plenty of applications, including autonomous driving perception, surveillance tasks, wearable devices or IoT networks. Object recognition using video data is more chal…
Autonomous DrivingObjectobject-detectionObject Detection+2Feature Flow: In-network Feature Flow Estimation for Video Object Detection
Optical flow, which expresses pixel displacement, is widely used in many computer vision tasks to provide pixel-level motion information. However, with the remarkable progress of the convolutional neural network, recent …
object-detectionObject DetectionOptical Flow EstimationVideo Object DetectionDual Semantic Fusion Network for Video Object Detection
Video object detection is a tough task due to the deteriorated quality of video sequences captured under complex environments. Currently, this area is dominated by a series of feature enhancement based methods, which dis…
Objectobject-detectionObject DetectionOptical Flow Estimation+1Survey of Machine Learning Accelerators
New machine learning accelerators are being announced and released each month for a variety of applications from speech recognition, video object detection, assisted driving, and many data center applications. This paper…
BIG-bench Machine Learningobject-detectionObject Detectionspeech-recognition+3Video Object Detection via Object-level Temporal Aggregation
While single-image object detectors can be naively applied to videos in a frame-by-frame fashion, the prediction is often temporally inconsistent. Moreover, the computation can be redundant since neighboring frames are i…
CPUObjectobject-detectionObject Detection+2Mining Inter-Video Proposal Relations for Video Object Detection
Recent studies have shown that, context aggregating information from proposals in different frames can clearly enhance the performance of video object detection. However, these approaches mainly exploit the intra-proposa…
Objectobject-detectionObject DetectionRelation+3CenterNet Heatmap Propagation for Real-time Video Object Detection
The existing methods for video object detection mainly depend on two-stage image object detectors. The fact that two-stage detectors are generally slow makes it difficult to apply in real-time scenarios. Moreover, adapti…
Objectobject-detectionObject DetectionVideo Object DetectionInstance-aware, Context-focused, and Memory-efficient Weakly Supervised Object Detection
Weakly supervised learning has emerged as a compelling tool for object detection by reducing the need for strong supervision during training. However, major challenges remain: (1) differentiation of object instances can …
Objectobject-detectionObject DetectionVideo Object Detection+2LiDAR-based Online 3D Video Object Detection with Graph-based Message Passing and Spatiotemporal Transformer Attention
Existing LiDAR-based 3D object detectors usually focus on the single-frame detection, while ignoring the spatiotemporal information in consecutive point cloud frames. In this paper, we propose an end-to-end online 3D vid…
Objectobject-detectionObject DetectionVideo Object DetectionMemory Enhanced Global-Local Aggregation for Video Object Detection
How do humans recognize an object in a piece of video? Due to the deteriorated quality of single frame, it may be hard for people to identify an occluded object in this frame by just utilizing information within one imag…
Objectobject-detectionObject DetectionVideo Object DetectionRN-VID: A Feature Fusion Architecture for Video Object Detection
Consecutive frames in a video are highly redundant. Therefore, to perform the task of video object detection, executing single frame detectors on every frame without reusing any information is quite wasteful. It is with …
Objectobject-detectionObject DetectionVideo Object DetectionPlug & Play Convolutional Regression Tracker for Video Object Detection
Video object detection targets to simultaneously localize the bounding boxes of the objects and identify their classes in a given video. One challenge for video object detection is to consistently detect all objects acro…
Objectobject-detectionObject Detectionregression+1Argus: Efficient Activity Detection System for Extended Video Analysis
We propose an Efficient Activity Detection System, Argus, for Extended Video Analysis in the surveillance scenario. For the spatial-temporal event detection in the surveillance video, we first generate video proposals by…
Action DetectionActivity DetectionEvent DetectionMulti-Object Tracking+5Detection and Tracking Meet Drones Challenge
Drones, or general UAVs, equipped with cameras have been fast deployed with a wide range of applications, including agriculture, aerial photography, and surveillance. Consequently, automatic understanding of visual data …
Multi-Object TrackingObjectobject-detectionObject Detection+2Rethinking Temporal Object Detection from Robotic Perspectives
Video object detection (VID) has been vigorously studied for years but almost all literature adopts a static accuracy-based evaluation, i.e., average precision (AP). From a robotic perspective, the importance of recall c…
Multi-Object TrackingObjectobject-detectionObject Detection+2Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection
In static monitoring cameras, useful contextual information can stretch far beyond the few seconds typical video understanding models might see: subjects may exhibit similar behavior over multiple days, and background ob…
object-detectionObject Detectionvehicle detectionVideo Object Detection+1Learning Where to Focus for Efficient Video Object Detection
Transferring existing image-based detectors to the video is non-trivial since the quality of frames is always deteriorated by part occlusion, rare pose, and motion blur. Previous approaches exploit to propagate and aggre…
Objectobject-detectionVideo Object DetectionObject Guided External Memory Network for Video Object Detection
Video object detection is more challenging than image object detection because of the deteriorated frame quality. To enhance the feature representation, state-of-the-art methods propagate temporal information into the de…
Hard AttentionObjectobject-detectionObject Detection+1