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Found 14 papers, 7 papers with code
DOA-Aware Audio-Visual Self-Supervised Learning for Sound Event Localization and Detection
In this task, one may train a deep neural network (DNN) using FOA data annotated with the classes and directions of arrival (DOAs) of sound events.
TeamTrack: A Dataset for Multi-Sport Multi-Object Tracking in Full-pitch Videos
Multi-object tracking (MOT) is a critical and challenging task in computer vision, particularly in situations involving objects with similar appearances but diverse movements, as seen in team sports.
INF: Implicit Neural Fusion for LiDAR and Camera
INF first trains a neural density field of the target scene using LiDAR frames.
Causal Effect Estimation on Hierarchical Spatial Graph Data
To address this problem, we propose a spatial intervention neural network (SINet) that leverages the hierarchical structure of spatial graphs to learn a rich representation of the covariates and the treatments and exploits this representation to predict a time series of treatment outcome.
Hierarchical Neural Memory Network for Low Latency Event Processing
Conventional architectures encode entire scene contents at a fixed rate regardless of their temporal characteristics.
Ranked #5 on
Object Detection
on GEN1 Detection
Speeding Up Multi-Objective Hyperparameter Optimization by Task Similarity-Based Meta-Learning for the Tree-Structured Parzen Estimator
Hyperparameter optimization (HPO) is a vital step in improving performance in deep learning (DL).
Efficient stereo matching on embedded GPUs with zero-means cross correlation
By combining this technique with the domain transformation (DT) algorithm, our system show real-time processing speed of 32 fps, on a Jetson Tx2 GPU for 1, 280x384 pixel images with a maximum disparity of 128.
How does AI play football? An analysis of RL and real-world football strategies
Recent advances in reinforcement learning (RL) have made it possible to develop sophisticated agents that excel in a wide range of applications.
Heterogeneous Grid Convolution for Adaptive, Efficient, and Controllable Computation
This paper proposes a novel heterogeneous grid convolution that builds a graph-based image representation by exploiting heterogeneity in the image content, enabling adaptive, efficient, and controllable computations in a convolutional architecture.
Grab the Reins of Crowds: Estimating the Effects of Crowd Movement Guidance Using Causal Inference
In this paper, we consider the problem of estimating the effects of crowd movement guidance from past data.
Warm Starting CMA-ES for Hyperparameter Optimization
Hyperparameter optimization (HPO), formulated as black-box optimization (BBO), is recognized as essential for automation and high performance of machine learning approaches.
Self-supervised Neural Audio-Visual Sound Source Localization via Probabilistic Spatial Modeling
By incorporating with the spatial information in multichannel audio signals, our method trains deep neural networks (DNNs) to distinguish multiple sound source objects.
Block-wise Scrambled Image Recognition Using Adaptation Network
In this study, a perceptually hidden object-recognition method is investigated to generate secure images recognizable by humans but not machines.
