Behaviour4All: in-the-wild Facial Behaviour Analysis Toolkit
원문 초록
In this paper, we introduce Behavior4All, a comprehensive, open-source toolkit for in-the-wild facial behavior analysis, integrating Face Localization, Valence-Arousal Estimation, Basic Expression Recognition and Action Unit Detection, all within a single framework. Available in both CPU-only and GPU-accelerated versions, Behavior4All leverages 12 large-scale, in-the-wild datasets consisting of over 5 million images from diverse demographic groups. It introduces a novel framework that leverages distribution matching and label co-annotation to address tasks with non-overlapping annotations, encoding prior knowledge of their relatedness. In the largest study of its kind, Behavior4All outperforms both state-of-the-art and toolkits in overall performance as well as fairness across all databases and tasks. It also demonstrates superior generalizability on unseen databases and on compound expression recognition. Finally, Behavior4All is way times faster than other toolkits.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
MathOptAI.jl: Embed trained machine learning predictors into JuMP models
ConsumerBench: Benchmarking Generative AI Applications on End-User Devices
Versatile and Fast Location-Based Private Information Retrieval with Fully Homomorphic Encryption over the Torus
SecONNds: Secure Outsourced Neural Network Inference on ImageNet
Plug-and-Play Linear Attention for Pre-trained Image and Video Restoration Models
FlashDMoE: Fast Distributed MoE in a Single Kernel
토론
이 논문과 연결된 포럼 글이 아직 없습니다.