Search Results for author:
Found 11 papers, 2 papers with code
Semantic-Supervised Spatial-Temporal Fusion for LiDAR-based 3D Object Detection
In this paper, we propose a novel Semantic-Supervised Spatial-Temporal Fusion (ST-Fusion) method, which introduces a novel fusion module to relieve the spatial misalignment caused by the object motion over time and a feature-level semantic supervision to sufficiently unlock the capacity of the proposed fusion module.
Unlock the Power of Unlabeled Data in Language Driving Model
Specifically, we first introduce a series of template-based prompts to extract scene information, generating questions that create pseudo-answers for the unlabeled data based on a model trained with limited labeled data.
Unify and Anchor: A Context-Aware Transformer for Cross-Domain Time Series Forecasting
The rise of foundation models has revolutionized natural language processing and computer vision, yet their best practices to time series forecasting remains underexplored.
UTSD: Unified Time Series Diffusion Model
In this paper, a Unified Time Series Diffusion (UTSD) model is established for the first time to model the multi-domain probability distribution, utilizing the powerful probability distribution modeling ability of Diffusion.
A Wave is Worth 100 Words: Investigating Cross-Domain Transferability in Time Series
Specifically, we transfer the time series data from different domains into a common spectral latent space, and enable the model to learn the temporal pattern knowledge of different domains directly from the common space and utilize it for the inference of downstream tasks, thereby mitigating the challenge of heterogeneous cross-domains migration.
GCoder: Improving Large Language Model for Generalized Graph Problem Solving
Furthermore, GCoder efficiently manages large-scale graphs with millions of nodes and diverse input formats, overcoming the limitations of previous models focused on the reasoning steps paradigm.
Tran-GCN: A Transformer-Enhanced Graph Convolutional Network for Person Re-Identification in Monitoring Videos
Person Re-Identification (Re-ID) has gained popularity in computer vision, enabling cross-camera pedestrian recognition.
DnSwin: Toward Real-World Denoising via Continuous Wavelet Sliding-Transformer
Real-world image denoising is a practical image restoration problem that aims to obtain clean images from in-the-wild noisy inputs.
Adaptive Processor Frequency Adjustment for Mobile Edge Computing with Intermittent Energy Supply
With astonishing speed, bandwidth, and scale, Mobile Edge Computing (MEC) has played an increasingly important role in the next generation of connectivity and service delivery.
Graph Wasserstein Correlation Analysis for Movie Retrieval
Spectral graph filtering is introduced to encode graph signals, which are then embedded as probability distributions in a Wasserstein space, called graph Wasserstein metric learning.
Graph Inference Learning for Semi-supervised Classification
In this work, we address semi-supervised classification of graph data, where the categories of those unlabeled nodes are inferred from labeled nodes as well as graph structures.
