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Found 10 papers, 0 papers with code
Gait Recognition from a Single Image using a Phase-Aware Gait Cycle Reconstruction Network
Specifically, a phase estimation network is introduced for the input single image, and the gait cycle reconstruction network exploits the estimated phase to mitigate the dependence of an encoded feature on the phase of that single image.
Extended Depth-of-Field Lensless Imaging using an Optimized Radial Mask
The freedom of design of coded masks used by mask-based lensless cameras is an advantage these systems have when compared to lens-based ones.
Descriptor-Free Multi-View Region Matching for Instance-Wise 3D Reconstruction
This paper proposes a multi-view extension of instance segmentation without relying on texture or shape descriptor matching.
Noisy-LSTM: Improving Temporal Awareness for Video Semantic Segmentation
Semantic video segmentation is a key challenge for various applications.
Probabilistic Plant Modeling via Multi-View Image-to-Image Translation
This paper describes a method for inferring three-dimensional (3D) plant branch structures that are hidden under leaves from multi-view observations.
Joint Intensity and Spatial Metric Learning for Robust Gait Recognition
This paper describes a joint intensity metric learning method to improve the robustness of gait recognition with silhouette-based descriptors such as gait energy images.
Material Classification Using Frequency- and Depth-Dependent Time-Of-Flight Distortion
This paper presents a material classification method using an off-the-shelf Time-of-Flight (ToF) camera.
Recovering Transparent Shape From Time-Of-Flight Distortion
This paper presents a method for recovering shape and normal of a transparent object from a single viewpoint using a Time-of-Flight (ToF) camera.
Recovering Inner Slices of Translucent Objects by Multi-Frequency Illumination
This paper describes a method for recovering appearance of inner slices of translucent objects.
Gait Recognition under Speed Transition
Given an input image sequence of speed transited gait of a test subject, we estimate the mapping matrix of the test subject as well as the phase and stride sequence using an energy minimization framework considering the following three points: (1) fitness of the synthesized images to the input image sequence as well as to an eigenspace constructed by exemplars of training subjects; (2) smoothness of the phase and the stride sequence; and (3) pitch and stride fitness to the pitch-stride preference model.
