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Found 9 papers, 6 papers with code
TDT Loss Takes It All: Integrating Temporal Dependencies among Targets into Non-Autoregressive Time Series Forecasting
Learning temporal dependencies among targets (TDT) benefits better time series forecasting, where targets refer to the predicted sequence.
ChangeAnywhere: Sample Generation for Remote Sensing Change Detection via Semantic Latent Diffusion Model
Remote sensing change detection (CD) is a pivotal technique that pinpoints changes on a global scale based on multi-temporal images.
SDSTrack: Self-Distillation Symmetric Adapter Learning for Multi-Modal Visual Object Tracking
Multimodal Visual Object Tracking (VOT) has recently gained significant attention due to its robustness.
Ranked #18 on
Rgb-T Tracking
on RGBT234
Targeted Representation Alignment for Open-World Semi-Supervised Learning
Open-world Semi-Supervised Learning aims to classify unlabeled samples utilizing information from labeled data while unlabeled samples are not only from the labeled known categories but also from novel categories previously unseen.
Generalized Label-Efficient 3D Scene Parsing via Hierarchical Feature Aligned Pre-Training and Region-Aware Fine-tuning
Deep neural network models have achieved remarkable progress in 3D scene understanding while trained in the closed-set setting and with full labels.
Generalized 3D Self-supervised Learning Framework via Prompted Foreground-Aware Feature Contrast
The second is that we prevent over-discrimination between 3D segments/objects and encourage grouped foreground-to-background distinctions at the segment level with adaptive feature learning in a Siamese correspondence network, which adaptively learns feature correlations within and across point cloud views effectively.
Economic Potential for Hybrid Electric Vehicles in Urban Signal-free Intersections with Decentralized MPC
The development of electric and connected vehicles as well as automated driving technologies are key towards the smart city, with convenient urban mobility and high energy economy performance.
AGMB-Transformer: Anatomy-Guided Multi-Branch Transformer Network for Automated Evaluation of Root Canal Therapy
Accurate evaluation of the treatment result on X-ray images is a significant and challenging step in root canal therapy since the incorrect interpretation of the therapy results will hamper timely follow-up which is crucial to the patients' treatment outcome.
High-Resolution Segmentation of Tooth Root Fuzzy Edge Based on Polynomial Curve Fitting with Landmark Detection
As the most economical and routine auxiliary examination in the diagnosis of root canal treatment, oral X-ray has been widely used by stomatologists.
