Saliency-Driven Versatile Video Coding for Neural Object Detection
Saliency-driven image and video coding for humans has gained importance in the recent past. In this paper, we propose such a saliency-driven coding framework for the video coding for machines task using the latest video coding standard Versatile Video Coding (VVC). To determine the salient regions before encoding, we employ the real-time-capable object detection network You Only Look Once~(YOLO) in combination with a novel decision criterion. To measure the coding quality for a machine, the state-of-the-art object segmentation network Mask R-CNN was applied to the decoded frame. From extensive simulations we find that, compared to the reference VVC with a constant quality, up to 29 % of bitrate can be saved with the same detection accuracy at the decoder side by applying the proposed saliency-driven framework. Besides, we compare YOLO against other, more traditional saliency detection methods.
Code (0)
등록된 구현이 없습니다.
Tasks
DecoderObjectobject-detectionObject DetectionSaliency DetectionSemantic SegmentationMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Saliency-Driven Hierarchical Learned Image Coding for Machines
We propose to employ a saliency-driven hierarchical neural image compression network for a machine-to-machine communication scenario following the compress-then-analyze paradigm. By that, different areas of the image are…
AllDecoderImage Compressionobject-detection+1TSalV360: A Method and Dataset for Text-driven Saliency Detection in 360-Degrees Videos
In this paper, we deal with the task of text-driven saliency detection in 360-degrees videos. For this, we introduce the TSV360 dataset which includes 16,000 triplets of ERP frames, textual descriptions of salient object…
Video Saliency DetectionImproving Video Compression With Deep Visual-Attention Models
Recent advances in deep learning have markedly improved the quality of visual-attention modelling. In this work we apply these advances to video compression. We propose a compression method that uses a saliency model t…
Video CompressionA Benchmark Dataset and Saliency-guided Stacked Autoencoders for Video-based Salient Object Detection
Image-based salient object detection (SOD) has been extensively studied in the past decades. However, video-based SOD is much less explored since there lack large-scale video datasets within which salient objects are una…
BenchmarkingObjectobject-detectionObject Detection+2Flow Guided Recurrent Neural Encoder for Video Salient Object Detection
Image saliency detection has recently witnessed significant progress due to deep convolutional neural networks. However, extending state-of-the-art saliency detectors from image to video is challenging. The performance o…
Objectobject-detectionObject DetectionOptical Flow Estimation+4