WestAI
  • About
    • Team
    • Network
  • Services
    • AI Consulting
    • AI Hardware
    • AI Training Courses
    • AI Test Platforms
  • Research
  • Updates
  • DE
Select Page

Physics-guided Shape-from-Template: Monocular Video Perception through Neural Surrogate Models

 3D reconstruction of dynamic scenes is a long-standing problem in computer graphics and increasingly difficult the less information is available. Shape-from-Template (SfT) methods aim to reconstruct a template-based geometry from RGB images or video sequences, often...

TraM-NeRF: Tracing Mirror and Near-Perfect Specular Reflections through Neural Radiance Fields

Implicit representations like Neural Radiance Fields (NeRF) showed impressive results for photorealistic rendering of complex scenes with fine details. However, ideal or near-perfectly specular reflecting objects such as mirrors, which are often encountered in various...

SLCF-Net: Sequential LiDAR-Camera Fusion for Semantic Scene Completion using a 3D Recurrent U-Net

We introduce SLCF-Net, a novel approach for the Semantic Scene Completion (SSC) task that sequentially fuses LiDAR and camera data. It jointly estimates missing geometry and semantics in a scene from sequences of RGB images and sparse LiDAR measurements. The images...

Learning from SAM: Harnessing a Foundation Model for Sim2Real Adaptation by Regularization

Domain adaptation is especially important for robotics applications, where target domain training data is usually scarce and annotations are costly to obtain. We present a method for self-supervised domain adaptation for the scenario where annotated source domain data...

Post-Processing Independent Evaluation of Sound Event Detection Systems

Due to the high variation in the application requirements of sound event detection (SED) systems, it is not sufficient to evaluate systems only in a single operating point. Therefore, the community recently adopted the polyphonic sound detection score (PSDS) as an...

pFedV: Mitigating Feature Distribution Skewness via Personalized Federated Learning with Variational Distribution Constraints

Statistical heterogeneity, especially feature distribution skewness, among the distributed data is a common phenomenon in practice, which is a challenging problem in federated learning that can lead to a degradation in the performance of the aggregated global model....
« Older Entries
Next Entries »
  • Contact
  • Publishing Notes
  • Data Protection
© WestAI 2025