Search Results for author:
Found 10 papers, 4 papers with code
SuperPC: A Single Diffusion Model for Point Cloud Completion, Upsampling, Denoising, and Colorization
We show that SuperPC outperforms the state-of-the-art specialized models as well as their combination on all four individual tasks.
VL-Nav: Real-time Vision-Language Navigation with Spatial Reasoning
Vision-language navigation in unknown environments is crucial for mobile robots.
Imperative Learning: A Self-supervised Neuro-Symbolic Learning Framework for Robot Autonomy
The framework of IL consists of three primary components: a neural module, a reasoning engine, and a memory system.
PhysORD: A Neuro-Symbolic Approach for Physics-infused Motion Prediction in Off-road Driving
To bridge this gap, we present PhysORD, a neural-symbolic approach integrating the conservation law, i. e., the Euler-Lagrange equation, into data-driven neural models for motion prediction in off-road driving.
Dynamic Domain Discrepancy Adjustment for Active Multi-Domain Adaptation
This mechanism controls the alignment level of features between each source domain and the target domain, effectively leveraging the local advantageous feature information within the source domains.
Multi-Source Unsupervised Domain Adaptation
Unsupervised Domain Adaptation
Alleviating the Long-Tail Problem in Conversational Recommender Systems
Conversational recommender systems (CRS) aim to provide the recommendation service via natural language conversations.
Multi-Granularity Detector for Vulnerability Fixes
To address these challenges and boost the effectiveness of prior works, we propose MiDas (Multi-Granularity Detector for Vulnerability Fixes).
Attention-Enhanced Cross-modal Localization Between 360 Images and Point Clouds
To overcome this limitation, we focus on correlating the information of 360 equirectangular images to point clouds, proposing an end-to-end learnable network to conduct cross-modal visual localization by establishing similarity in high-dimensional feature space.
Self-attention Comparison Module for Boosting Performance on Retrieval-based Open-Domain Dialog Systems
Since the pre-trained language models are widely used, retrieval-based open-domain dialog systems, have attracted considerable attention from researchers recently.
Using Vivado-HLS for Structural Design: a NoC Case Study
Ultimately, we succeeded in using Vivado-HLS to produce router and NoC modules that are exact cycle- and bit-accurate replacements of our reference RTL-based router and NoC modules.
Hardware Architecture
