Traditional frame-based cameras inevitably suffer from motion blur due to long exposure
times. As a kind of bio-inspired camera, the event camera records the intensity changes in …

Abstract Neural Radiance Fields (NeRF) achieves impressive ren-dering performance by
learning volumetric 3D representation from several images of different views. However, it is …

The performance of video frame interpolation is inherently correlated with the ability to
handle motion in the input scene. Even though previous works recognize the utility of …

Abstract Video Frame Interpolation (VFI) aims to generate intermediate video frames
between consecutive input frames. Since the event cameras are bio-inspired sensors that …

DAVIS camera, streaming two complementary sensing modalities of asynchronous events
and frames, has gradually been used to address major object detection challenges (eg, fast …

Traditional cameras produce desirable vision results but struggle with motion blur in high-
speed scenes due to long exposure windows. Existing frame-based deblurring algorithms …

With frame-based cameras, capturing fast-moving scenes without suffering from blur often
comes at the cost of low SNR and low contrast. Worse still, the photometric constancy that …

Abstract Neural Radiance Fields (NeRFs) have shown great potential in novel view
synthesis. However they struggle to render sharp images when the data used for training is …

Modern image-based deblurring methods usually show degenerate performance in low-light
conditions since the images often contain most of the poorly visible dark regions and a few …

Motion deblurring from a blurred image is a challenging computer vision problem because
frame-based cameras lose information during the blurring process. Several attempts have …