Since the advent of social media platforms, image selection based on social preference is a challenging task that all users inherently undertake before sharing images with the public. In our user study for this problem, human choices of images based on perceived social preference are largely inaccurate (58.7% accuracy). The challenge of this task, also known as image popularity assessment, lies in its subjective nature caused by visual and non-visual factors. Especially in the social media setting, social feedback on a particular image largely differs depending on who uploads it. Therefore social preference model should be able to account for this user-specific image aspect of the task. To address this issue, we present a retrieval-augmented approach that leverages both image features and user-specific statistics for neural image popularity assessment. User-specific statistics are derived by retrieving past images with their statistics from a memory bank. By combining these statistics with image features, our approach achieves 79.5% accuracy, which significantly outperforms human and baseline models on the pairwise ranking of images from the Instagram Influencer Dataset. Our source code will be publicly available.

Robotic orthoses have potential to assist people having difficulty in walking due to their neurological disorders. However, it is important to design lighter orthoses since additional weight and inertia from the device cause discomfort to the wearer and even instability during walking in some extreme cases. To address this problem, a robotic orthosis with a cable differential mechanism is proposed in this paper. It is designed to assist stroke patients with hemiplegia. It has 2 active degrees of freedom at the hip and knee joints and one passive degree of freedom at the ankle. A cable differential mechanism is used to transmit the torques generated by the actuators, which are located near the pelvis of the wearer to reduce the inertial effect. The cable differential mechanism allows for the actuators to share the load with each other, which results in decrease of the maximum required torques by the actuators. Therefore, smaller actuators are possible to be used for further reduction of the weight. The proposed robotic orthosis with a cable differential mechanism, which is called “COWALK-Mobile 2,” is implemented and evaluated.