4 citations · 5 across the 3 of their papers we have counts for
4 papers
Object-centric Cross-modal Feature Distillation for Event-based Object Detection
Lei Li, Alexander Liniger, Mario Millhaeusler +3
Event cameras are gaining popularity due to their unique properties, such as their low latency and high dynamic range. One task where these benefits can be crucial is real-time obj…
Leveraging 2D Data to Learn Textured 3D Mesh Generation
Paul Henderson, Vagia Tsiminaki, Christoph H. Lampert
Numerous methods have been proposed for probabilistic generative modelling of 3D objects. However, none of these is able to produce textured objects, which renders them of limited…
Learned Multi-View Texture Super-Resolution
Audrey Richard, Ian Cherabier, Martin R. Oswald +3
We present a super-resolution method capable of creating a high-resolution texture map for a virtual 3D object from a set of lower-resolution images of that object. Our architectur…
3D Appearance Super-Resolution with Deep Learning
Yawei Li, Vagia Tsiminaki, Radu Timofte +2
We tackle the problem of retrieving high-resolution (HR) texture maps of objects that are captured from multiple view points. In the multi-view case, model-based super-resolution (…