3 accepted papers
This paper presents a novel monitoring framework that infers the level of collision risk for autonomous vehicles (AV s) based on their object detection performance. The framework takes two sets of predictions from different algorithms and associates their inconsistencies with the collision risk via
Diffusion models have achieved great success in generating 2D images. However, the quality and generalizability of 3D content generation remain limited. State-of-the-art methods often require large-scale 3D assets for training, which are challenging to collect. In this work, we introduce Kiss3DGen (…
We propose a voxel-based optimization framework ReVoRF for few-shot radiance fields that strategically addresses the unreliability in pseudo novel view synthesis. Our method pivots on the insight that relative depth relationships within neighboring regions are more reliable than the absolute color v…