8 accepted papers
Most of the existing methods for video understanding primarily focus on videos only lasting tens of seconds, with limited exploration of techniques for handling long videos. The increased number of frames in long videos poses two main challenges: difficulty in locating key information and performing…
Autonomous robot systems have attracted increasing research attention in recent years where environment understanding is a crucial step for robot navigation human-robot interaction and decision. Real-world robot systems usually collect visual data from multiple sensors and are required to recognize…
Efficiently and accurately detecting people from 3D point cloud data is of great importance in many robotic and autonomous driving applications. This fundamental perception task is still very challenging due to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/199
Effectively encoding multi-scale contextual information is crucial for accurate semantic segmentation. Most of the existing transformer-based segmentation models combine features across scales without any selection, where features on sub-optimal scales may degrade segmentation outcomes. Leveraging f…
Object proposal generation is an important and fundamental task in computer vision. In this paper, we propose ProposalCLIP, a method towards unsupervised open-category object proposal generation. Unlike previous works which require a large number of bounding box annotations and/or can only generate…
Object detection combines object classification and object localization problems. Most existing object detection methods usually locate objects by leveraging regression networks trained with Smooth L1 loss function to predict offsets between candidate boxes and objects. However, this loss function a…
Scene Parsing is a challenging task in computer vision, which can be formulated as a pixel-wise classification problem. Existing deep-learning-based methods usually use one general classifier to recognize all object categories. However, the general classifier easily makes some mistakes in dealing wi…
Referring expression image segmentation aims to segment out the object referred by a natural language query expression. Without considering the specific properties of visual and textual information, existing works usually deal with this task by directly feeding a foreground/background classifier wit…