Search Results for author:
Found 12 papers, 3 papers with code
Deep Material Recognition in Light-Fields via Disentanglement of Spatial and Angular Information
Light-field cameras capture sub-views from multiple perspectives simultaneously, with possibly reflectance variations that can be used to augment material recognition in remote sensing, autonomous driving, etc.
Leveraging Compressed Frame Sizes For Ultra-Fast Video Classification
Classifying videos into distinct categories, such as Sport and Music Video, is crucial for multimedia understanding and retrieval, especially when an immense volume of video content is being constantly generated.
Judging a video by its bitstream cover
Classifying videos into distinct categories, such as Sport and Music Video, is crucial for multimedia understanding and retrieval, especially in an age where an immense volume of video content is constantly being generated.
Efficient Semantic Segmentation by Altering Resolutions for Compressed Videos
In this paper, we propose an altering resolution framework called AR-Seg for compressed videos to achieve efficient VSS.
Phocus: Picking Valuable Research from a Sea of Citations
The global influential factor of the reference to the citing paper is the product of the local influential factor and the total influential factor of the citing paper.
Learning to compose 6-DoF omnidirectional videos using multi-sphere images
The system utilizes conventional omnidirectional VR camera footage directly without the need for a depth map or segmentation mask, thereby significantly simplifying the overall complexity of the 6-DoF omnidirectional video composition.
Novel tile segmentation scheme for omnidirectional video
Regular omnidirectional video encoding technics use map projection to flatten a scene from a spherical shape into one or several 2D shapes.
Learning to Estimate Kernel Scale and Orientation of Defocus Blur with Asymmetric Coded Aperture
Consistent in-focus input imagery is an essential precondition for machine vision systems to perceive the dynamic environment.
Online Multi-modal Person Search in Videos
The task of searching certain people in videos has seen increasing potential in real-world applications, such as video organization and editing.
Learning Model-Blind Temporal Denoisers without Ground Truths
Denoisers trained with synthetic data often fail to cope with the diversity of unknown noises, giving way to methods that can adapt to existing noise without knowing its ground truth.
AGEM: Solving Linear Inverse Problems via Deep Priors and Sampling
In this paper we propose to use a denoising autoencoder (DAE) prior to simultaneously solve a linear inverse problem and estimate its noise parameter.
Long and Diverse Text Generation with Planning-based Hierarchical Variational Model
Existing neural methods for data-to-text generation are still struggling to produce long and diverse texts: they are insufficient to model input data dynamically during generation, to capture inter-sentence coherence, or to generate diversified expressions.
