6 accepted papers
With the rapid evolution of Large Language Models (LLMs), multi-round workflows, such as autonomous agents and iterative retrieval, have become increasingly prevalent. However, this raises hurdles for serving LLMs under prefill-decode (PD) disaggregation, a widely adopted paradigm that separates the…
Flexible tendon-driven multi-segment robotic bronchoscopes can reach peripheral lung regions for minimally invasive diagnosis and therapy. However, long tendon transmissions introduce friction, elasticity, and backlash, which couple the motion of adjacent segments and reduce operational accuracy and…
To minimize irrelevant and redundant information in tactile data and harness the dexterity of human hands. In this paper, we introduce a novel binary classification network with normalized differential convolution (NDConv) layers. Our method leverages the recent progress in visual-based tactile sens
This paper proposes a novel 3D single-object tracker to more stably, accurately, and faster track objects, even if they are temporarily missed. Our idea is to utilize spatial-temporal data association to achieve object tracking robustly, and it consists of two main parts. We firstly employ a tempora…
Most existing text spotting methods either focus on horizontal/oriented texts or perform arbitrary shaped text spotting with character-level annotations. In this paper, we propose a novel text spotting framework to detect and recognize text of arbitrary shapes in an end-to-end manner, using only wor…
In this paper, we first provide a new perspective to divide existing high performance object detection methods into direct and indirect regressions. Direct regression performs boundary regression by predicting the offsets from a given point, while indirect regression predicts the offsets from some b…