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Found 9 papers, 3 papers with code
Controllable Group Choreography using Contrastive Diffusion
Music-driven group choreography poses a considerable challenge but holds significant potential for a wide range of industrial applications.
Improved statistical benchmarking of digital pathology models using pairwise frames evaluation
Nested pairwise frames is a method for relative benchmarking of cell or tissue digital pathology models against manual pathologist annotations on a set of sampled patches.
MoViT: Memorizing Vision Transformers for Medical Image Analysis
We evaluate our method on a public histology image dataset and an in-house MRI dataset, demonstrating that MoViT applied to varied medical image analysis tasks, can outperform vanilla transformer models across varied data regimes, especially in cases where only a small amount of annotated data is available.
Music-Driven Group Choreography
The proposed dataset consists of 16. 7 hours of paired music and 3D motion from in-the-wild videos, covering 7 dance styles and 16 music genres.
Style Transfer for 2D Talking Head Animation
In this paper, we present a new method to generate talking head animation with learnable style references.
A Quantum Neural Network Regression for Modeling Lithium-ion Battery Capacity Degradation
Given the high power density low discharge rate and decreasing cost rechargeable lithium-ion batteries LiBs have found a wide range of applications such as power grid level storage systems electric vehicles and mobile devices.
Analyze the Effects of COVID-19 on Energy Storage Systems: A Techno-Economic Approach
During the COVID-19 pandemic, the U. S. power sector witnessed remarkable electricity demand changes in many geographical regions.
Uncertainty-aware Label Distribution Learning for Facial Expression Recognition
In this paper, we propose a new uncertainty-aware label distribution learning method to improve the robustness of deep models against uncertainty and ambiguity.
Facial Expression Recognition
Facial Expression Recognition (FER)
Global-Local Attention for Emotion Recognition
Our network is designed to extract features from both facial and context regions independently, then learn them together using the attention module.
