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Can Shape-Infused Joint Embeddings Improve Image-Conditioned 3D Diffusion?
We find that, while matching CLIP in generation quality and diversity, CISP substantially improves coherence with input images, underscoring the value of incorporating 3D knowledge into generative models.
RadarLCD: Learnable Radar-based Loop Closure Detection Pipeline
The methodology undergoes evaluation across a variety of FMCW Radar dataset scenes, and it is compared to state-of-the-art systems such as Scan Context for Place Recognition and ICP for Loop Closure.
Continual Cross-Dataset Adaptation in Road Surface Classification
Accurate road surface classification is crucial for autonomous vehicles (AVs) to optimize driving conditions, enhance safety, and enable advanced road mapping.
IC3D: Image-Conditioned 3D Diffusion for Shape Generation
To address this limitation and enhance image-guided 3D DDPMs with augmented 3D understanding, we introduce CISP (Contrastive Image-Shape Pre-training), obtaining a well-structured image-shape joint embedding space.
