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cs.CV2024
Cohere3D: Exploiting Temporal Coherence for Unsupervised Representation Learning of Vision-based Autonomous Driving
Yichen Xie, Hongge Chen, Gregory P. Meyer +6
Due to the lack of depth cues in images, multi-frame inputs are important for the success of vision-based perception, prediction, and planning in autonomous driving. Observations f…
cs.CV2023
SHIFT3D: Synthesizing Hard Inputs For Tricking 3D Detectors
Hongge Chen, Zhao Chen, Gregory P. Meyer +4
We present SHIFT3D, a differentiable pipeline for generating 3D shapes that are structurally plausible yet challenging to 3D object detectors. In safety-critical applications like…
cs.CV2023
NOVA: NOvel View Augmentation for Neural Composition of Dynamic Objects
Dakshit Agrawal, Jiajie Xu, Siva Karthik Mustikovela +3
We propose a novel-view augmentation (NOVA) strategy to train NeRFs for photo-realistic 3D composition of dynamic objects in a static scene. Compared to prior work, our framework s…