12 accepted papers
In this paper, we explore incremental few-shot object detection (iFSD), which incrementally learns novel classes using only a few examples without revisiting base classes. Previous iFSD works achieved the desired results by applying metalearning. However, meta-learning approaches show insufficient p…
Aspect-based sentiment analysis (ABSA) is a task of identifying fine-grained sentiment entities in a given sentence, which is generally formulated as a sequence labeling problem. Recently, advancements in large pre-trained language models (PLMs) led to generative ABSA, where the task is treated as t…
The goal of intelligent embodied agents is to learn how to explore within the environment, interact with objects, and understand the environment in order to achieve task objectives. There are two main approaches to training such agents: one is to train an action policy that performs the task goal th…
Accurate change detection enables a wide range of tasks in visual surveillance, anomaly detection and mobile robotics. However, contemporary change detection approaches assume an ideal matching between the current and stored scenes, whereas only coarse matching is possible in real-world scenarios. T…
Autoregressive transformer (ART)-based grapheme-to-phoneme (G2P) models have been proposed for bi/multilingual text-to-speech systems. Although they have achieved great success, they suffer from high inference latency in real-time industrial applications, especially processing long sentence. In this…
Accurate estimation of 3D geometry and camera motion enables a wide range of tasks in robotics and autonomous vehicles. However, the lack of semantics and the performance degradation due to dynamic objects hinder its application to real-world scenarios. To overcome these limitations, we design a nov
We present a challenging dataset, ChangeSim, aimed at online scene change detection (SCD) and more. The data is collected in photo-realistic simulation environments with the presence of environmental non-targeted variations, such as air turbidity and light condition changes, as well as targeted obje…
With the development of text-to-speech technology, high-quality voices can be heard in AI speaker responses, car navigation guidance, and news article-reading services. As services become more diverse, domains are expanded, requiring fast and high-performance grapheme-to-phoneme (G2P) technology. In…
Contemporary soft keyboards possess limitations: the lack of physical feedback results in an increase of typos, and the interface of soft keyboards degrades the utility of the screen. To overcome these limitations, we propose an Invisible Mobile Keyboard (IMK), which lets users freely type on the de…
This paper presents Reoriented Short-Cuts (RSC): A modification of the traditional Short-Cut technique, allowing almost sure, single homotopy class, asymptotic convergence in high degree of freedom (DoF) problems. An additional Informed Gaussian Sampling (IGS) technique is also introduced for conver…
To perform a home service task through cooperation with a human in a real environment, a robot needs to deal with the environmental changes and accordingly plan appropriate behavior sequence. For this purpose, in this paper, we propose an adaptive task planner which is based on memory and reasoning.…
This paper presents a fire heading estimation for solving the autonomous navigation problem of a firefighting robot in smoke-filled indoor fire environment. In smoke-filled fire environments, firefighters and firefighting robots experience difficulty maintaining direction while finding the fire sour…