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Found 4 papers, 2 papers with code
Facial Affect Analysis: Learning from Synthetic Data & Multi-Task Learning Challenges
Facial affect analysis remains a challenging task with its setting transitioned from lab-controlled to in-the-wild situations.
Directional Deep Embedding and Appearance Learning for Fast Video Object Segmentation
We propose a directional deep embedding and appearance learning (DDEAL) method, which is free of the online fine-tuning process, for fast VOS.
Multiple receptive fields and small-object-focusing weakly-supervised segmentation network for fast object detection
To address this problem, we propose a multiple receptive field and small-object-focusing weakly-supervised segmentation network (MRFSWSnet) to achieve fast object detection.
Adversarial Feature Sampling Learning for Efficient Visual Tracking
The tracking-by-detection framework usually consist of two stages: drawing samples around the target object in the first stage and classifying each sample as the target object or background in the second stage.
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