As an emerging and challenging problem in the computer vision community, weakly
supervised object localization and detection plays an important role for developing new …

GeoAI, or geospatial artificial intelligence, has become a trending topic and the frontier for
spatial analytics in Geography. Although much progress has been made in exploring the …

Localizing objects in image collections without supervision can help to avoid expensive
annotation campaigns. We propose a simple approach to this problem, that leverages the …

Weakly supervised object localization (WSOL) is a challenging problem when given image
category labels but requires to learn object localization models. Optimizing a convolutional …

Weakly-supervised temporal action localization aims to recognize and localize action
segments in untrimmed videos given only video-level action labels for training. Without the …

Unsupervised object re-identification targets at learning discriminative representations for
object retrieval without any annotations. Clustering-based methods conduct training with the …

Sketches are highly expressive, inherently capturing subjective and fine-grained visual
cues. The exploration of such innate properties of human sketches has, however, been …

Abstract Weakly Supervised Object Detection (WSOD) has emerged as an effective tool to
train object detectors using only the image-level category labels. However, without object …

In this paper, we describe a graph-based algorithm that uses the features obtained by a self-
supervised transformer to detect and segment salient objects in images and videos. With this …

Abstract 3D multi-object tracking in LiDAR point clouds is a key ingredient for self-driving
vehicles. Existing methods are predominantly based on the tracking-by-detection pipeline …