Search
Results
-
Structured Bird's-Eye-View Traffic Scene Understanding from Onboard Images
(2021)2021 IEEE/CVF International Conference on Computer Vision (ICCV)Autonomous navigation requires structured representation of the road network and instance-wise identification of the other traffic agents. Since the traffic scene is defined on the ground plane, this corresponds to scene understanding in the bird's-eye-view (BEV). However, the onboard cameras of autonomous cars are customarily mounted horizontally for a better view of the surrounding, making this task very challenging. In this work, we ...Conference Paper -
Scaling Semantic Segmentation Beyond 1K Classes on a Single GPU
(2021)2021 IEEE/CVF International Conference on Computer Vision (ICCV)The state-of-the-art object detection and image classification methods can perform impressively on more than 9k classes. In contrast, the number of classes in semantic segmentation datasets is relatively limited. This is not surprising when the restrictions caused by the lack of labeled data and high computation demand for segmentation are considered. In this paper, we propose a novel training methodology to train and scale the existing ...Conference Paper -
Towards Efficient Graph Convolutional Networks for Point Cloud Handling
(2021)2021 IEEE/CVF International Conference on Computer Vision (ICCV)We aim at improving the computational efficiency of graph convolutional networks (GCNs) for learning on point clouds. The basic graph convolution that is composed of a K-nearest neighbor (KNN) search and a multilayer perceptron (MLP) is examined. By mathematically analyzing the operations there, two findings to improve the efficiency of GCNs are obtained. (1) The local geometric structure information of 3D representations propagates ...Conference Paper -
Mining Relations Among Cross-Frame Affinities for Video Semantic Segmentation
(2022)Lecture Notes in Computer Science ~ Computer Vision – ECCV 2022The essence of video semantic segmentation (VSS) is how to leverage temporal information for prediction. Previous efforts are mainly devoted to developing new techniques to calculate the cross-frame affinities such as optical flow and attention. Instead, this paper contributes from a different angle by mining relations among cross-frame affinities, upon which better temporal information aggregation could be achieved. We explore relations ...Conference Paper -
pixel+: integrating and standardizing of various interactive single-camera, multi-light imagery
(2020)Proceedings of SPIE ~ Optics, Photonics and Digital Technologies for Imaging Applications VIMulti-light, single-camera imaging techniques like Reflectance Transformation Imaging (RTI, including PTM, HSH, and PCA-RBF) and the Portable Light Dome (PLD) have been used by cultural heritage scholars and collection curators extensively because of the extra interactive visual information that can be revealed on artefacts when compared to standard digital photography. Besides a virtual relighting of the scanned object, these techniques ...Conference Paper -
Spectral Tensor Train Parameterization of Deep Learning Layers
(2021)Proceedings of Machine Learning Research ~ Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS 2021)We study low-rank parameterizations of weight matrices with embedded spectral properties in the Deep Learning context. The low-rank property leads to parameter efficiency and permits taking computational shortcuts when computing mappings. Spectral properties are often subject to constraints in optimization problems, leading to better models and stability of optimization. We start by looking at the compact SVD parameterization of weight ...Conference Paper -
WILDTRACK: A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection
(2018)2018 IEEE/CVF Conference on Computer Vision and Pattern RecognitionPeople detection methods are highly sensitive to occlusions between pedestrians, which are extremely frequent in many situations where cameras have to be mounted at a limited height. The reduction of camera prices allows for the generalization of static multi-camera set-ups. Using joint visual information from multiple synchronized cameras gives the opportunity to improve detection performance. In this paper, we present a new large-scale ...Conference Paper -
Deep Extreme Cut: From Extreme Points to Object Segmentation
(2018)2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)This paper explores the use of extreme points in an object (left-most, right-most, top, bottom pixels) as input to obtain precise object segmentation for images and videos. We do so by adding an extra channel to the image in the input of a convolutional neural network (CNN), which contains a Gaussian centered in each of the extreme points. The CNN learns to transform this information into a segmentation of an object that matches those ...Conference Paper -
Classification-Driven Dynamic Image Enhancement
(2018)2018 IEEE/CVF Conference on Computer Vision and Pattern RecognitionConvolutional neural networks rely on image texture and structure to serve as discriminative features to classify the image content. Image enhancement techniques can be used as preprocessing steps to help improve the overall image quality and in turn improve the overall effectiveness of a CNN. Existing image enhancement methods, however, are designed to improve the perceptual quality of an image for a human observer. In this paper, we are ...Conference Paper -
Conditional Probability Models for Deep Image Compression
(2018)2018 IEEE/CVF Conference on Computer Vision and Pattern RecognitionDeep Neural Networks trained as image auto-encoders have recently emerged as a promising direction for advancing the state-of-the-art in image compression. The key challenge in learning such networks is twofold: To deal with quantization, and to control the trade-off between reconstruction error (distortion) and entropy (rate) of the latent image representation. In this paper, we focus on the latter challenge and propose a new technique ...Conference Paper