A Generalized Framework for Video Instance Segmentation

The handling of long videos with complex and occluded sequences has recently emerged as a new challenge in the video instance segmentation (VIS) community. However, existing methods have limitations in addressing this challenge. We argue that the biggest bottleneck in current approaches is the discrepancy between training and inference. To effectively bridge this gap, we propose a Generalized framework for VIS, namely GenVIS, that achieves state-of-the-art performance on challenging benchmarks without designing complicated architectures or requiring extra post-processing. The key contribution of GenVIS is the learning strategy, which includes a query-based training pipeline for sequential learning with a novel target label assignment. Additionally, we introduce a memory that effectively acquires information from previous states. Thanks to the new perspective, which focuses on building relationships between separate frames or clips, GenVIS can be flexibly executed in both online and semi-online manner. We evaluate our approach on popular VIS benchmarks, achieving state-of-the-art results on YouTube-VIS 2019/2021/2022 and Occluded VIS (OVIS). Notably, we greatly outperform the state-of-the-art on the long VIS benchmark (OVIS), improving 5.6 AP with ResNet-50 backbone. Code is available at https://github.com/miranheo/GenVIS.Comment: CVPR 202

Fast and Stable Ionic Electroactive Polymer Actuators with PEDOT:PSS/(Graphene–Ag-Nanowires) Nanocomposite Electrodes

Ionic electroactive polymer (IEAP) actuators that are driven by electrical stimuli have been widely investigated for use in practical applications. However, conventional electrodes in IEAP actuators have a serious drawback of poor durability under long-term actuation in open air, mainly because of leakage of the inner electrolyte and hydrated cations through surface cracks on the metallic electrodes. To overcome this problem, a top priority is developing new high-performance ionic polymer actuators with graphene electrodes that have superior mechanical, electrical conductivity, and electromechanical properties. However, the task is made difficultby issues such as the low electrical conductivity of graphene (G). The percolation network of silver nanowires (Ag-NWs) is believed to enhance the conductivity of graphene, while poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS), which exhibits excellent stability under ambient conditions, is expected to improve the actuation performance of IEAP actuators. In this study, we developed a very fast, stable, and durable IEAP actuator by employing electrodes made of a nanocomposite comprising PEDOT:PSS and graphene–Ag-NWs (P/(G–Ag)). The cost-effective P/(G–Ag) electrodes with high electrical conductivity displayed a smooth surface resulting from the PEDOT:PSS coating, which prevented oxidation of the surface upon exposure to air, and showedstrong bonding between the ionic polymer and the electrode surface. More interestingly, the proposed IEAP actuator based on the P/G–Ag electrode can be used in active biomedical devices, biomimetic robots, wearable electronics, and flexible soft electronics

Active EMI Reduction Using Chaotic Modulation in a Buck Converter with Relaxed Output LC Filter

DC-DC buck converters are widely used in portable applications because of their high power efficiency. However, their inherent fast switching releases electromagnetic emissions, making them prominent sources of electromagnetic interference (EMI). This paper proposes a voltage-controlled buck converter that reduces EMI by using a chaotic pulse-width modulation (PWM) technique based on a chaotic triangular ramp generator. The chaotic triangular ramp generator is constructed from a simple on-chip chaotic circuit linked with a symmetrically triangular ramp circuit. The proposed converter can thus operate in the chaotic mode reducing the EMI without requiring any EMI filters. Additionally, using the triangular ramp signal can relax the requirement for a large LC output filter in chaotic mode. The effectiveness of the proposed scheme was experimentally verified with a chaotic triangular ramp generator embedded in a voltage-mode controller buck converter using a 0.18 µm Complementary Metal Oxide Semiconductor (CMOS) process. The measurement results from a prototype showed that the EMI improvement from the proposed scheme is approximately 14.53 dB at the fundamental switching frequency with respect to the standard fixed-frequency PWM reference case