Papers Video Object Detection
“Video Object Detection” 태그가 달린 논문 159편 · 필터 해제
FFAVOD: Feature Fusion Architecture for Video Object Detection
A significant amount of redundancy exists between consecutive frames of a video. Object detectors typically produce detections for one image at a time, without any capabilities for taking advantage of this redundancy. Me…
Objectobject-detectionObject DetectionVideo Object DetectionTemporal RoI Align for Video Object Recognition
Video object detection is challenging in the presence of appearance deterioration in certain video frames. Therefore, it is a natural choice to aggregate temporal information from other frames of the same video into the …
Instance SegmentationObjectobject-detectionObject Detection+4TF-Blender: Temporal Feature Blender for Video Object Detection
Video objection detection is a challenging task because isolated video frames may encounter appearance deterioration, which introduces great confusion for detection. One of the popular solutions is to exploit the tempora…
Objectobject-detectionObject DetectionVideo Object DetectionTemporal Early Exits for Efficient Video Object Detection
Transferring image-based object detectors to the domain of video remains challenging under resource constraints. Previous efforts utilised optical flow to allow unchanged features to be propagated, however, the overhead …
Objectobject-detectionObject DetectionOptical Flow Estimation+1SGE net: Video object detection with squeezed GRU and information entropy map
Recently, deep learning based video object detection has attracted more and more attention. Compared with object detection of static images, video object detection is more challenging due to the motion of objects, while …
Objectobject-detectionObject DetectionVideo Object DetectionEnd-to-End Video Object Detection with Spatial-Temporal Transformers
Recently, 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 detectors. However, …
Objectobject-detectionObject DetectionOptical Flow Estimation+1Few-Shot Video Object Detection
We introduce Few-Shot Video Object Detection (FSVOD) with three contributions to real-world visual learning challenge in our highly diverse and dynamic world: 1) a large-scale video dataset FSVOD-500 comprising of 500 cl…
DiversityFew-Shot LearningFew-Shot Video Object DetectionObject+3Emerging Properties in Self-Supervised Vision Transformers
In this paper, we question if self-supervised learning provides new properties to Vision Transformer (ViT) that stand out compared to convolutional networks (convnets). Beyond the fact that adapting self-supervised metho…
Copy DetectionImage ClassificationImage RetrievalLinear evaluation+7Motion Vector Extrapolation for Video Object Detection
Despite the continued successes of computationally efficient deep neural network architectures for video object detection, performance continually arrives at the great trilemma of speed versus accuracy versus computation…
CPUGPUMotion EstimationObject+4Short-term anchor linking and long-term self-guided attention for video object detection
We present a new network architecture able to take advantage of spatio-temporal information available in videos to boost object detection precision. First, box features are associated and aggregated by linking proposals …
Objectobject-detectionObject DetectionVideo Object DetectionHoughNet: Integrating near and long-range evidence for visual detection
This paper presents HoughNet, a one-stage, anchor-free, voting-based, bottom-up object detection method. Inspired by the Generalized Hough Transform, HoughNet determines the presence of an object at a certain location by…
3D Object DetectionImage GenerationInstance SegmentationKeypoint Detection+6When Few-Shot Learning Meets Video Object Detection
Different from static images, videos contain additional temporal and spatial information for better object detection. However, it is costly to obtain a large number of videos with bounding box annotations that are requir…
Few-Shot LearningFew-Shot Video Object DetectionObjectobject-detection+3Real-Time and Accurate Object Detection in Compressed Video by Long Short-term Feature Aggregation
Video object detection is a fundamental problem in computer vision and has a wide spectrum of applications. Based on deep networks, video object detection is actively studied for pushing the limits of detection speed and…
GPUObjectobject-detectionObject Detection+2PatchNet -- Short-range Template Matching for Efficient Video Processing
Object recognition is a fundamental problem in many video processing tasks, accurately locating seen objects at low computation cost paves the way for on-device video recognition. We propose PatchNet, an efficient convol…
Objectobject-detectionObject DetectionObject Recognition+5New Generation Deep Learning For Video Object Dection:A Survery
Video object detection, a basic task in the computer vision field, is rapidly evolving and widely used. In recent years, deep learning methods have rapidly become widespread in the field of video object detection, achiev…
Deep LearningObjectobject-detectionObject Detection+1Temporal-Channel Transformer for 3D Lidar-Based Video Object Detection in Autonomous Driving
The strong demand of autonomous driving in the industry has lead to strong interest in 3D object detection and resulted in many excellent 3D object detection algorithms. However, the vast majority of algorithms only mode…
3D Object DetectionAutonomous DrivingDecoderObject+3An Analysis of Deep Object Detectors For Diver Detection
With the end goal of selecting and using diver detection models to support human-robot collaboration capabilities such as diver following, we thoroughly analyze a large set of deep neural networks for diver detection. We…
object-detectionObject DetectionVideo Object DetectionJoint Representation of Temporal Image Sequences and Object Motion for Video Object Detection
In this paper, we propose a new video object detector (VoD) method referred to as temporal feature aggregation and motion-aware VoD (TM-VoD), which produces a joint representation of temporal image sequences and object m…
Objectobject-detectionObject DetectionVideo Object DetectionRecurrent Neural Networks for video object detection
There is lots of scientific work about object detection in images. For many applications like for example autonomous driving the actual data on which classification has to be done are videos. This work compares different…
Autonomous DrivingObjectobject-detectionObject Detection+1Object-aware Feature Aggregation for Video Object Detection
We present an Object-aware Feature Aggregation (OFA) module for video object detection (VID). Our approach is motivated by the intriguing property that video-level object-aware knowledge can be employed as a powerful sem…
Objectobject-detectionObject DetectionObject Recognition+1