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Found 17 papers, 5 papers with code
ADL4D: Towards A Contextually Rich Dataset for 4D Activities of Daily Living
However, existing datasets for 4D HOI (3D HOI over time) are limited to one subject inter- acting with one object only.
Adapting Learned Image Codecs to Screen Content via Adjustable Transformations
As learned image codecs (LICs) become more prevalent, their low coding efficiency for out-of-distribution data becomes a bottleneck for some applications.
HAROOD: Human Activity Classification and Out-of-Distribution Detection with Short-Range FMCW Radar
We propose HAROOD as a short-range FMCW radar-based human activity classifier and out-of-distribution (OOD) detector.
Care3D: An Active 3D Object Detection Dataset of Real Robotic-Care Environments
As labor shortage increases in the health sector, the demand for assistive robotics grows.
HOOD: Real-Time Human Presence and Out-of-Distribution Detection Using FMCW Radar
HOOD solves the human presence and OOD detection problems simultaneously in a single pipeline.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
Efficient Contextformer: Spatio-Channel Window Attention for Fast Context Modeling in Learned Image Compression
Entropy estimation is essential for the performance of learned image compression.
Remote Task-oriented Grasp Area Teaching By Non-Experts through Interactive Segmentation and Few-Shot Learning
We receive grasp area demonstrations for a new task via interactive segmentation, and learn from these few demonstrations to estimate the required grasp area on an unseen scene for the given task.
MCROOD: Multi-Class Radar Out-Of-Distribution Detection
The simple idea is called respiration detector (RESPD) and eases the OOD detection, especially for human sitting and standing classes.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
Reconstruction-based Out-of-Distribution Detection for Short-Range FMCW Radar
Out-of-distribution (OOD) detection recently has drawn attention due to its critical role in the safe deployment of modern neural network architectures in real-world applications.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
Bounding Box Disparity: 3D Metrics for Object Detection With Full Degree of Freedom
The most popular evaluation metric for object detection in 2D images is Intersection over Union (IoU).
Evaluation of Video Coding for Machines without Ground Truth
To mitigate this problem, we propose an evaluation method based on pseudo ground-truth data from the field of semantic segmentation to the evaluation of video coding for machines.
Contextformer: A Transformer with Spatio-Channel Attention for Context Modeling in Learned Image Compression
Entropy modeling is a key component for high-performance image compression algorithms.
Color Image Demosaicking Using a 3-Stage Convolutional Neural Network Structure
Color demosaicking (CDM) is a critical first step for the acquisition of high-quality RGB images with single chip cameras.
Noise-resistant Deep Learning for Object Classification in 3D Point Clouds Using a Point Pair Descriptor
To address this issue, we propose a point pair descriptor that is robust to noise and occlusion and achieves high retrieval accuracy.
Deep Learning for Surface Material Classification Using Haptic And Visual Information
When a user scratches a hand-held rigid tool across an object surface, an acceleration signal can be captured, which carries relevant information about the surface.
A System for Precise End-to-End Delay Measurements in Video Communication
To judge the quality of the video transmission in such a system, it is important to be able to precisely measure the end-to-end (E2E) delay of the transmitted video.
Multimedia
Keypoint Encoding for Improved Feature Extraction from Compressed Video at Low Bitrates
As a result, the bitrate of the side information related to keypoint encoding is significantly reduced.
