10 accepted papers
Open Vocabulary Human-Object Interaction (HOI) detection aims to detect interactions between humans and objects while generalizing to novel interaction classes beyond the training set. Current methods often rely on Vision and Language Models (VLMs) but face challenges due to suboptimal image encoder…
Monocular 3D object tracking methods are widely employed in robotic applications, however, they often struggle with low-contrast image sequences. In this paper, we introduce a novel approach to filtering redundant edges in images by leveraging sparse interior correspondences. Our method features a s
Dynamic Scene Graph Generation (DSGG) aims to create a scene graph for each video frame by detecting objects and predicting their relationships. Weakly Supervised DSGG (WS-DSGG) reduces annotation workload by using an un- localized scene graph from a single frame per video for training. Existing WS-…
Integrating external tools into Large Foundation Models (LFMs) has emerged as a promising approach to enhance their problem-solving capabilities. While existing studies have demonstrated strong performance in tool-augmented Visual Question Answering (VQA), recent benchmarks re- veal significant gaps…
"Zero-shot Human-Object Interaction (HOI) detection has emerged as a frontier topic due to its capability to detect HOIs beyond a predefined set of categories. This task entails not only identifying the interactiveness of human-object pairs and localizing them but also recognizing both seen and unse…
Open-vocabulary human-object interaction (HOI) detection which is concerned with the problem of detecting novel HOIs guided by natural language is crucial for understanding human-centric scenes. However prior zero-shot HOI detectors often employ the same levels of feature maps to model HOIs with var…
The Novel Category Discovery problem aims to cluster an unlabeled set with the help of a labeled set consisting of disjoint but related classes. However, existing models treat class names as discrete one-hot labels and ignore the semantic understanding of these classes. In this paper, we propose a n…
Human Object Interaction (HOI) detection aims to localize and infer the relationships between a human and an object. Arguably, training supervised models for this task from scratch presents challenges due to the performance drop over rare classes and the high computational cost and time required to…
Understanding human tasks through video observations is an essential capability of intelligent agents. The challenges of such capability lie in the difficulty of generating a detailed understanding of situated actions, their effects on object states (\ie, state changes), and their causal dependencie…
In order to change the positioning method “teach-playback” for tube-to-tubesheet welding by robots, this letter proposes an autonomous positioning method based on coordinate transformation and template matching. The coordinate trans-formation between the robot coordinate system (RCS) and the drawing