Audiovisual slowfast networks for video recognition
We present Audiovisual SlowFast Networks, an architecture for integrated audiovisual
perception. AVSlowFast has Slow and Fast visual pathways that are deeply integrated with a …
perception. AVSlowFast has Slow and Fast visual pathways that are deeply integrated with a …
Unidentified video objects: A benchmark for dense, open-world segmentation
Current state-of-the-art object detection and segmentation methods work well under the
closed-world assumption. This closed-world setting assumes that the list of object categories …
closed-world assumption. This closed-world setting assumes that the list of object categories …
Relative attributing propagation: Interpreting the comparative contributions of individual units in deep neural networks
Abstract As Deep Neural Networks (DNNs) have demonstrated superhuman performance in
a variety of fields, there is an increasing interest in understanding the complex internal …
a variety of fields, there is an increasing interest in understanding the complex internal …
Gaussian dynamic convolution for efficient single-image segmentation
Interactive single-image segmentation is ubiquitous in the scientific and commercial imaging
software. Lightweight neural network is one practical and effective way to accomplish the …
software. Lightweight neural network is one practical and effective way to accomplish the …
A comprehensive review of image retargeting
With the development of display technologies, image retargeting plays a significant role in
computer vision and pattern recognition communities currently. Image retargeting aims to …
computer vision and pattern recognition communities currently. Image retargeting aims to …
Class-agnostic object detection
Object detection models perform well at localizing and classifying objects that they are
shown during training. However, due to the difficulty and cost associated with creating and …
shown during training. However, due to the difficulty and cost associated with creating and …
Benchmarking algorithms for food localization and semantic segmentation
The problem of food segmentation is quite challenging since food is characterized by
intrinsic high intra-class variability. Also, segmentation of food images taken in-the-wild may …
intrinsic high intra-class variability. Also, segmentation of food images taken in-the-wild may …
Multi-Sensor-Based Action Monitoring and Recognition via Hybrid Descriptors and Logistic Regression
In the fields of body-worn sensors and computer vision, current research is being done to
track and detect falls and activities of daily living using the automatic recognition of human …
track and detect falls and activities of daily living using the automatic recognition of human …
Robotic waste sorter with agile manipulation and quickly trainable detector
Owing to human labor shortages, the automation of labor-intensive manual waste-sorting is
needed. The goal of automating waste-sorting is to replace the human role of robust …
needed. The goal of automating waste-sorting is to replace the human role of robust …
Optical flow estimation from a single motion-blurred image
In most of computer vision applications, motion blur is regarded as an undesirable artifact.
However, it has been shown that motion blur in an image may have practical interests in …
However, it has been shown that motion blur in an image may have practical interests in …