7 accepted papers
Many Vision-Language-Action (VLA) models flatten image patches into a 1D token sequence, weakening the 2D spatial cues needed for precise manipulation. We introduce IVRA, a lightweight, training-free method that improves spatial understanding by exploiting affinity hints already available in the mod…
Pre-trained weights have become a cornerstone of modern deep learning, enabling efficient knowledge transfer and improving downstream task performance, especially in data-scarce scenarios. However, a fundamental question remains: how can we obtain better pre-trained weights that encapsulate more kno
In artificial intelligence (AI), many legal conflicts have arisen, especially concerning privacy and copyright associated with training data. When an AI model's training data incurs privacy concerns, it becomes imperative to develop a new model devoid of influences from such contentious data. Howeve…
Recent significant advancements in diffusion models have revolutionized image generation, enabling the synthesis of highly realistic images with text-based guidance. These breakthroughs have paved the way for constructing datasets via generative artificial intelligence (AI), offering immense potenti…
Recent complicated problems require large-scale datasets and complex model architectures, however, it is difficult to train such large networks due to high computational issues. Significant efforts have been made to make the training more efficient such as momentum, learning rate scheduling, weight…
Deep learning, based on which many modern algorithms operate, is well known to be data-hungry. In particular, the datasets appropriate for the intended application are difficult to obtain. To cope with this situation, we introduce a new dataset called ETRI-Activity3D, focusing on the daily activitie…
Facial expression recognition is increasingly gaining importance in emerging affective computing applications. In practice, achieving accurate facial expression recognition is still challenging due to environmental variations. In this paper, we propose a color channel-wise recurrent facial feature l…