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Titlebook: Advances in Visual Computing; 17th International S George Bebis,Bo Li,Remco Chang Conference proceedings 2022 The Editor(s) (if applicable)

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樓主: Jaundice
51#
發(fā)表于 2025-3-30 12:09:21 | 只看該作者
https://doi.org/10.1007/978-3-030-26407-9roxy for the missing gradients. We further improve invariance to nuisance factors by adding the discriminative task of predicting attributes. Our extensive evaluation highlights that when only a holistic representation is learned, we consistently outperform the state-of-the-art on the three most cha
52#
發(fā)表于 2025-3-30 15:34:03 | 只看該作者
https://doi.org/10.1007/978-3-030-26407-9 in a simple way, modeling each target’s trajectory separately, without the use of complex social interactions between humans or interactions between targets and the scene. Experimental results show that our method overall outperforms previous state-of-the-art methods, and yields better results in c
53#
發(fā)表于 2025-3-30 19:32:14 | 只看該作者
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發(fā)表于 2025-3-30 22:22:29 | 只看該作者
55#
發(fā)表于 2025-3-31 03:09:00 | 只看該作者
Biomimetic Oculomotor Control with?Spiking Neural Networkselop and train a biomimetic, SNN-driven, neuromuscular oculomotor controller for a realistic biomechanical model of the human eye. Event-based data flow in the SNN directs the necessary extraocular-muscle-actuated eye movements. We train our SNN models from scratch using modified deep learning techn
56#
發(fā)表于 2025-3-31 07:30:40 | 只看該作者
57#
發(fā)表于 2025-3-31 10:18:09 | 只看該作者
58#
發(fā)表于 2025-3-31 16:13:40 | 只看該作者
Photobombing Removal Benchmarking remove the photobombing from taken images to produce a pleasing image. In this paper, the aim is to conduct a benchmark on this aforementioned problem. To this end, we first collect a dataset of images with undesired and distracting elements which requires the removal of photobombing. Then, we anno
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