metropolitan
发表于 2025-3-23 13:34:44
Learning an Efficient Multimodal Depth Completion Model, but still faces some problems. First, the fusion of multimodal information requires more network modules to process different modalities. But the application scenarios of sparse ToF measurements usually demand lightweight structure and low computational cost. Second, fusing sparse and noisy depth
Decongestant
发表于 2025-3-23 14:39:20
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山羊
发表于 2025-3-23 20:48:05
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性上瘾
发表于 2025-3-24 00:03:57
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Mucosa
发表于 2025-3-24 06:22:37
YOLO5Face: Why Reinventing a Face Detectorted for the detection of face, we treat face detection as a general object detection task. We implement a face detector based on YOLOv5 object detector and call it YOLO5Face. We add a five-point landmark regression head into it and use the Wing loss function. We design detectors with different model
丰满有漂亮
发表于 2025-3-24 09:17:04
Counterfactual Fairness for Facial Expression Recognitionlity has been proposed as a method to address the problem of bias, giving rise to the popularity of using counterfactuals as a bias mitigation tool. In this paper, we undertake a systematic investigation of the usage of counterfactuals to achieve both statistical and causal-based fairness in facial
朴素
发表于 2025-3-24 11:53:02
Improved Cross-Dataset Facial Expression Recognition by Handling Data Imbalance and Feature Confusioicit domain shift between different datasets. In addition, FER data is naturally highly imbalanced, with a majority of the samples belonging to few expressions like neutral, happy and relatively fewer samples coming from expressions like disgust, fear, etc., which makes the FER task even more challe
不可知论
发表于 2025-3-24 16:25:31
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Femish
发表于 2025-3-24 21:08:15
YOLO5Face: Why Reinventing a Face Detectorresults on the WiderFace dataset show that our face detectors can achieve state-of-the-art performance in almost all the Easy, Medium, and Hard subsets, exceeding the more complex designated face detectors. The code is available at ..
重画只能放弃
发表于 2025-3-25 02:33:47
0302-9743 e 17th European Conference on Computer Vision, ECCV 2022. The conference took place in Tel Aviv, Israel, during October 23-27, 2022; the workshops were held hybrid or online..The 367 full papers included in this volume set were carefully reviewed and selected for inclusion in the ECCV 2022 workshop