8 accepted papers
Recently, 3D Gaussian Splatting (3DGS) has garnered significant attention for its remarkable capacity to efficiently synthesize novel views with high fidelity. Nevertheless, 3DGS encounters challenges in accurately representing the geometry of real-world scenes. To address this issue, previous metho
Value alignment, which aims to ensure that large language models (LLMs) and other AI agents behave in accordance with human values, is critical for ensuring safety and trustworthiness of these systems. A key component of value alignment is the modeling of human preferences as a representation of hum…
Human-Object Interaction (HOI) Detection constitutes an important aspect of human-centric scene understanding which requires precise object detection and interaction recognition. Despite increasing advancement in detection recognizing subtle and intricate interactions remains challenging. Recent met…
In this paper, we introduce DA <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{2}$</tex-math></inline-formula> , the first large-scale dual-arm dexterity-aware dataset for the generation of optimal bimanual grasp
We propose Differentiable Temporal Logic (DTL), a model-agnostic framework that introduces temporal constraints to deep networks. DTL treats the outputs of a network as a truth assignment of a temporal logic formula, and computes a temporal logic loss reflecting the consistency between the output an…
We propose the Motion Capsule Autoencoder (MCAE), which addresses a key challenge in the unsupervised learning of motion representations: transformation invariance. MCAE models motion in a two-level hierarchy. In the lower level, a spatio-temporal motion signal is divided into short, local, and sema…
In this work, we aim to leverage prior symbolic knowledge to improve the performance of deep models. We propose a graph embedding network that projects propositional formulae (and assignments) onto a manifold via an augmented Graph Convolutional Network (GCN). To generate semantically-faithful embed…
This paper addresses the motion planning problem for a team of aerial agents under high level goals. We propose a hybrid control strategy that guarantees the accomplishment of each agent's local goal specification, which is given as a temporal logic formula, while guaranteeing inter-agent collision…