9 accepted papers
Generating 3D meshes from a single image is an important but ill-posed task. Existing methods mainly adopt 2D multiview diffusion models to generate intermediate multiview images, and use the Large Reconstruction Model (LRM) to create the final meshes. However, the multiview images exhibit local inc…
We introduce Monarch Sparse Tuning (MoST), the first reparameterization-based parameter-efficient fine-tuning (PEFT) method tailored for 3D representation learning. Unlike existing adapter-based and prompt-tuning 3D PEFT methods, MoST introduces no additional inference overhead and is compatible wit…
Enabling Large Language Models (LLMs) to comprehend the 3D physical world remains a significant challenge. Due to the lack of large-scale 3D-text pair datasets, the success of LLMs has yet to be replicated in 3D understanding. In this paper, we rethink this issue and propose a new task: 3D Data-Effi…
Recent advancements in deep learning have greatly enhanced 3D object recognition, but most models are limited to closed-set scenarios, unable to handle unknown samples in real-world applications. Open-set recognition (OSR) addresses this limitation by enabling models to both classify known classes a…
Existing point cloud semantic segmentation networks cannot identify unknown classes and update their knowledge due to a closed-set and static perspective of the real world which would induce the intelligent agent to make bad decisions. To address this problem we propose a Probability-Driven Framewor…
Humans solving algorithmic (or) reasoning problems typically exhibit solution times that grow as a function of problem difficulty. Adaptive recurrent neural networks have been shown to exhibit this property for various language-processing tasks. However, little work has been performed to assess whe…
Semantic scene completion (SSC) aims to complete a partial 3D scene and predict its semantics simultaneously. Most existing works adopt the voxel representations, thus suffering from the growth of memory and computation cost as the voxel resolution increases. Though a few works attempt to solve SSC…
Supernumerary robotic limbs (SRL) are new types of wearable robots used as the third limb to work with humans. The device is designed to provide the wearer with better auxiliary ability. This paper presents the design and implementation of a Series-Parallel-Reconfigurable Tendon-driven Supernumerary
Hypertension is one of the most important contributors to heart disease and stroke. Multimodality medical image fusion plays an important role in the precise diagnosis, treatment planning and follow-up studies of various diseases. In this paper, we propose an image fusion framework in patients with…