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Found 7 papers, 0 papers with code
Scalable Video Object Segmentation with Simplified Framework
The current popular methods for video object segmentation (VOS) implement feature matching through several hand-crafted modules that separately perform feature extraction and matching.
Improved Fine-Tuning by Better Leveraging Pre-Training Data
The generalization result of using pre-training data shows that the excess risk bound on a target task can be improved when the appropriate pre-training data is included in fine-tuning.
Modeling Noisy Annotations for Crowd Counting
The annotation noise in crowd counting is not modeled in traditional crowd counting algorithms based on crowd density maps.
Accelerating Monte Carlo Bayesian Inference via Approximating Predictive Uncertainty over the Simplex
In this work, assuming that the exact posterior or a decent approximation is obtained, we propose a generic framework to approximate the output probability distribution induced by model posterior with a parameterized model and in an amortized fashion.
Crowd Counting by Adaptively Fusing Predictions from an Image Pyramid
In this paper, in contrast to using filters of different sizes, we utilize an image pyramid to deal with scale variations.
Incorporating Side Information by Adaptive Convolution
For example, for crowd counting, the camera perspective (e. g., camera angle and height) gives a clue about the appearance and scale of people in the scene.
Video Desnowing and Deraining Based on Matrix Decomposition
The existing snow/rain removal methods often fail for heavy snow/rain and dynamic scene.
