114 citations · 300 across the 12 of their papers we have counts for
10 papers · 1 filter
BinsFormer: Revisiting Adaptive Bins for Monocular Depth Estimation
Zhenyu Li, Xuyang Wang, Xianming Liu +1
Monocular depth estimation is a fundamental task in computer vision and has drawn increasing attention. Recently, some methods reformulate it as a classification-regression task to…
AutoPose: Searching Multi-Scale Branch Aggregation for Pose Estimation
Xinyu Gong, Wuyang Chen, Yifan Jiang +5
We present AutoPose, a novel neural architecture search(NAS) framework that is capable of automatically discovering multiple parallel branches of cross-scale connections towards ac…
FasterSeg: Searching for Faster Real-time Semantic Segmentation
Wuyang Chen, Xinyu Gong, Xianming Liu +3
We present FasterSeg, an automatically designed semantic segmentation network with not only state-of-the-art performance but also faster speed than current methods. Utilizing neura…
Real Time Visual Tracking using Spatial-Aware Temporal Aggregation Network
Tao Hu, Lichao Huang, Xianming Liu +1
More powerful feature representations derived from deep neural networks benefit visual tracking algorithms widely. However, the lack of exploitation on temporal information prevent…
Depth Restoration: A fast low-rank matrix completion via dual-graph regularization
Wenxiang Zuo, Qiang Li, Xianming Liu
As a real scenes sensing approach, depth information obtains the widespread applications. However, resulting from the restriction of depth sensing technology, the depth map capture…
Connecting Image Denoising and High-Level Vision Tasks via Deep Learning
Ding Liu, Bihan Wen, Jianbo Jiao +3
Image denoising and high-level vision tasks are usually handled independently in the conventional practice of computer vision, and their connection is fragile. In this paper, we co…
Mapping the world population one building at a time
Tobias G. Tiecke, Xianming Liu, Amy Zhang +8
High resolution datasets of population density which accurately map sparsely-distributed human populations do not exist at a global scale. Typically, population data is obtained us…
Building Detection from Satellite Images on a Global Scale
Amy Zhang, Xianming Liu, Andreas Gros +1
In the last several years, remote sensing technology has opened up the possibility of performing large scale building detection from satellite imagery. Our work is some of the firs…
When Image Denoising Meets High-Level Vision Tasks: A Deep Learning Approach
Ding Liu, Bihan Wen, Xianming Liu +2
Conventionally, image denoising and high-level vision tasks are handled separately in computer vision. In this paper, we cope with the two jointly and explore the mutual influence…
Feedback Neural Network for Weakly Supervised Geo-Semantic Segmentation
Xianming Liu, Amy Zhang, Tobias Tiecke +2
Learning from weakly-supervised data is one of the main challenges in machine learning and computer vision, especially for tasks such as image semantic segmentation where labeling…