11 accepted papers
The recent emergence of extreme climate events has significantly raised awareness about sustainable living. In addition to developing energy-saving materials and technologies, existing research mainly relies on traditional methods that encourage behavioral shifts towards sustainability, which can be…
Multimodal Sentiment Analysis (MSA) aims to predict sentiment from diverse data types, such as video, audio, and language. Recent progress in Multimodal Large Language Models (MLLMs) have demonstrated impressive performance across various tasks. However, in MSA, the increase in computational costs d…
Health and longevity are topics of great interest, leading to an exploration of the Japanese concept of ikigai, known for its impact on a fulfilling, extended life. Ikigai levels are dynamic, changing with personal growth and life situations, but traditional assessment methods are time-consuming, di…
As Industrial 4.0 unfolds and digital twin technology rapidly advances, modeling techniques that can abstract real-world industrial objects into accurate and robust models, referred to modeling for industrial objects (MIO) tasks, have become increasingly crucial. However, existing works still face t
Differentiable rendering has paved the way to training neural networks to perform “inverse graphics” tasks such as predicting 3D geometry from monocular photographs. To train high performing models, most of the current approaches rely on multi-view imagery which are not readily available in practice…
We present a method, Neural Radiance Flow (NeRFlow), to learn a 4D spatial-temporal representation of a dynamic scene from a set of RGB images. Key to our approach is the use of a neural implicit representation that learns to capture the 3D occupancy, radiance, and dynamics of the scene. By enforcin…
Cross-domain recommendation methods usually transfer knowledge across different domains implicitly, by sharing model parameters or learning parameter mappings in the latent space. Differing from previous studies, this paper focuses on learning explicit mapping between a user's behaviors (i.e. intera…
This paper presents a method of computing free motions of a planar assembly of rigid bodies connected by loose joints. Joints are modeled using local distance constraints, which are then linearized with respect to configuration space velocities, yielding a linear programming formulation that allows…
This paper explores a problem of reconfiguration of a large set of agents using global control signals: right, left, up and down. A field of obstacles guides the reconfiguration by limiting motion in the various directions. This paper extends work by Becker et al. ([4], [5] and [7]), and shows there…
This paper explores the problem of building a structure of a desired shape, using re-usable interlocking blocks. Blocks are cubes; we make use of nine different types of cubes, each with different arrangements of male and female connectors on the six sides of the cube. The desired shape is specified…
This paper presents a definition of convexity useful for describing local optimality in configuration spaces, proves that finding convex regions is relatively easy, and presents an algorithm for approximating the free configuration space using a set of such convex regions. The paper examines simple…