318 citations · 356 across the 4 of their papers we have counts for
5 papers
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
Yin Zhou, Oncel Tuzel
Accurate detection of objects in 3D point clouds is a central problem in many applications, such as autonomous navigation, housekeeping robots, and augmented/virtual reality. To in…
Attentional Network for Visual Object Detection
Kota Hara, Ming-Yu Liu, Oncel Tuzel +1
We propose augmenting deep neural networks with an attention mechanism for the visual object detection task. As perceiving a scene, humans have the capability of multiple fixation…
Global-Local Face Upsampling Network
Oncel Tuzel, Yuichi Taguchi, John R. Hershey
Face hallucination, which is the task of generating a high-resolution face image from a low-resolution input image, is a well-studied problem that is useful in widespread applicati…
Deep Hierarchical Parsing for Semantic Segmentation
Abhishek Sharma, Oncel Tuzel, David W. Jacobs
This paper proposes a learning-based approach to scene parsing inspired by the deep Recursive Context Propagation Network (RCPN). RCPN is a deep feed-forward neural network that ut…
Efficient Upsampling of Natural Images
Chinmay Hegde, Oncel Tuzel, Fatih Porikli
We propose a novel method of efficient upsampling of a single natural image. Current methods for image upsampling tend to produce high-resolution images with either blurry salient…