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Surface Normal Clustering for Implicit Representation of Manhattan Scenes
Nikola Popovic, Danda Pani Paudel, Luc Van Gool
Novel view synthesis and 3D modeling using implicit neural field representation are shown to be very effective for calibrated multi-view cameras. Such representations are known to…
Advancing Learned Video Compression with In-loop Frame Prediction
Ren Yang, Radu Timofte, Luc Van Gool
Recent years have witnessed an increasing interest in end-to-end learned video compression. Most previous works explore temporal redundancy by detecting and compressing a motion ma…
ManiFlow: Implicitly Representing Manifolds with Normalizing Flows
Janis Postels, Martin Danelljan, Luc Van Gool +1
Normalizing Flows (NFs) are flexible explicit generative models that have been shown to accurately model complex real-world data distributions. However, their invertibility constra…
AVisT: A Benchmark for Visual Object Tracking in Adverse Visibility
Mubashir Noman, Wafa Al Ghallabi, Daniya Najiha +7
One of the key factors behind the recent success in visual tracking is the availability of dedicated benchmarks. While being greatly benefiting to the tracking research, existing b…
Refign: Align and Refine for Adaptation of Semantic Segmentation to Adverse Conditions
David Bruggemann, Christos Sakaridis, Prune Truong +1
Due to the scarcity of dense pixel-level semantic annotations for images recorded in adverse visual conditions, there has been a keen interest in unsupervised domain adaptation (UD…
L2E: Lasers to Events for 6-DoF Extrinsic Calibration of Lidars and Event Cameras
Kevin Ta, David Bruggemann, Tim Brödermann +2
As neuromorphic technology is maturing, its application to robotics and autonomous vehicle systems has become an area of active research. In particular, event cameras have emerged…