Many computer end-users, such as research scientists and business analysts, need to
frequently query a database, yet lack enough programming knowledge to write a correct SQL …

Previous studies on multi-instance learning typically treated instances in the bags as
independently and identically distributed. The instances in a bag, however, are rarely independent …

Large-scale pre-training vision-language models (VLM) such as CLIP has demonstrated
outstanding performance in zero-shot classification, eg achieving 76.3% top-1 accuracy on …

Over the last years, the robotics community has made substantial progress in detection and
3D pose estimation of known and unknown objects. However, the question of how to identify …

Multi-label learning deals with data associated with multiple labels simultaneously. Previous
work on multi-label learning assumes that for each instance, the “full” label set associated …

This paper addresses the challenge of reconstructing a scene with a neural radiance field (NeRF)
for robot vision and scene understanding using multiple modalities. Researchers have …

Hierarchies of concepts are useful in many applications from navigation to organization of
objects. Usually, a hierarchy is created in a centralized manner by employing a group of …

To improve the generalization of 3D human pose estimators, many existing deep learning
based models focus on adding different augmentations to training poses. However, data …

In order to take full advantage of the properties of SiC (silicon carbide) materials at high
temperatures, the characteristics of common-source and differential amplifier circuits composed …

Accurate per-pixel semantic class annotations of the entire video are crucial for designing and
evaluating video semantic segmentation algorithms. However, the annotations are usually …