Results 231 to 240 of about 4,496,548 (308)

Depth Map Restoration From Undersampled Data

IEEE Transactions on Image Processing, 2017
Depth map sensed by low-cost active sensor is often limited in resolution, whereas depth information achieved from structure from motion or sparse depth scanning techniques may result in a sparse point cloud. Achieving a high-resolution (HR) depth map from a low resolution (LR) depth map or densely reconstructing a sparse non-uniformly sampled depth ...
Srimanta Mandal, Arnav Bhavsar, Anil Kumar Sao   +2 more
openaire   +3 more sources

Spherical Space Feature Decomposition for Guided Depth Map Super-Resolution

IEEE International Conference on Computer Vision, 2023
Guided depth map super-resolution (GDSR), as a hot topic in multi-modal image processing, aims to upsample low-resolution (LR) depth maps with additional information involved in high-resolution (HR) RGB images from the same scene.
Zixiang Zhao, Jiangshe Zhang, X. Gu, Chengli Tan, Shuang Xu, Yulun Zhang, R. Timofte, L. Gool   +7 more
semanticscholar   +1 more source

Depth map guided triplet network for deepfake face detection

Neural Networks, 2022
The widespread dissemination of facial forgery technology has brought many ethical issues and aroused widespread concern in society. Most research today treats deepfake detection as a fine grained classification task, which however makes it difficult to ...
Buyun Liang, Zhongyuan Wang, Baojin Huang, Qin Zou, Qian Wang, Jingjing Liang   +5 more
semanticscholar   +1 more source

Dense Depth-Map Estimation Based on Fusion of Event Camera and Sparse LiDAR

IEEE Transactions on Instrumentation and Measurement, 2022
Depth-map estimation reflects the geometry of the visible surface in the environment directly and plays an important role in perception and decision for intelligent robots.
Mingyue Cui, Yuzhang Zhu, Yechang Liu, Yun-Meng Liu, Gang Chen, Kai Huang   +5 more
semanticscholar   +1 more source

Depth Map Recovery Based on a Unified Depth Boundary Distortion Model

IEEE Transactions on Image Processing, 2022
Depth maps acquired by either physical sensors or learning methods are often seriously distorted due to boundary distortion problems, including missing, fake, and misaligned boundaries (compared with RGB images).
Haotian Wang, Meng Yang, Xuguang Lan, Ce Zhu, Nanning Zheng   +4 more
semanticscholar   +1 more source

Frequency-Dependent Depth Map Enhancement via Iterative Depth-Guided Affine Transformation and Intensity-Guided Refinement

IEEE transactions on multimedia, 2021
Recently, deep convolutional neural network sho-ws significant improvement for intensity-guided depth map enhancement. The most networks focus on either increasing depth or easing features propagation via residual learning and dense connection.
Y. Zuo, Yuming Fang, P. An, Xiwu Shang, Junnan Yang   +4 more
semanticscholar   +1 more source

Depth map super-resolution

2011 IEEE 19th Signal Processing and Communications Applications Conference (SIU), 2011
The objective of this work is to increase the range resolution of time-of-flight (ToF) cameras. Our work aims to produce a super-resolution depth map and reduce the depth error within the whole work volume using a novel multi-exposure data acquisition technique and Projection Onto Convex Sets(POCS) reconstruction.
Murat Gevrekci, Kubilay Pakin
openaire   +1 more source

Occlusion-Aware Depth Map Coding Optimization Using Allowable Depth Map Distortions

IEEE Transactions on Image Processing, 2019
In depth map coding, rate-distortion optimization for those pixels that will cause occlusion in view synthesis is a rather challenging task, since the synthesis distortion estimation is complicated by the warping competition and the occlusion order can be easily changed by the adopted optimization strategy.
Pan Gao, Aljosa Smolic
openaire   +2 more sources