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Found 7 papers, 0 papers with code
Object Tracking using Spatio-Temporal Networks for Future Prediction Location
To facilitate the future prediction ability, we follow three key observations: 1) object motion trajectory is affected significantly by camera motion; 2) the past trajectory of an object can act as a salient cue to estimate the object motion in the spatial domain; 3) previous frames contain the surroundings and appearance of the target object, which is useful for predicting the target object’s future locations.
Imaging through multimode fibres with physical prior
The role of the physical prior is to simplify the mapping relationship between the speckle pattern and the target image, thereby reducing the computational complexity.
ITRE: Low-light Image Enhancement Based on Illumination Transmission Ratio Estimation
In this paper, we propose a novel Retinex-based method, called ITRE, which suppresses noise and artifacts from the origin of the model, prevents over-exposure throughout the enhancement process.
Hyperspectral Image Super-Resolution via Dual-domain Network Based on Hybrid Convolution
Moreover, to further improve the perceptual quality of HSI, a frequency loss(HFL) is introduced to optimize the model in the frequency domain.
Gradient Domain Weighted Guided Image Filtering
Guided image filter is a well-known local filter in image processing.
Object Tracking Using Spatio-Temporal Future Prediction
Our trajectory prediction module predicts the target object's locations in the current and future frames based on the object's past trajectory.
Thermal Infrared Colorization via Conditional Generative Adversarial Network
Transforming a thermal infrared image into a realistic RGB image is a challenging task.
