11 accepted papers
Reconstructing High Dynamic Range (HDR) video from alternately exposed Low Dynamic Range (LDR) frames is challenged by large motion, exposure-induced photometric inconsistency, and information loss in saturated or under-exposed regions. Prior HDR video pipelines typically follow an alignment-reconst
Long-distance depth imaging holds great promise for applications such as autonomous driving and robotics. Direct time-of-flight (dToF) imaging offers high-precision, long-distance depth sensing, yet demands ultra-short pulse light sources and high-resolution time-to-digital converters. In contrast,…
Scene-aware Adaptive Compressive Sensing (ACS) has constituted a persistent pursuit holding substantial promise for the enhancement of Compressive Sensing (CS) performance. Cascaded ACS furnishes a proficient multi-stage framework for adaptively allocating the CS sampling based on previous CS measur…
iToF is a prevalent cost-effective technology for 3D perception. While its reliance on multi-measurement commonly leads to reduced performance in dynamic environments. Based on the analysis of the physical iToF imaging process we propose the iToF flow composed of crossmode transformation and uni-mod…
Existing rain image editing methods focus on either removing rain from rain images or rendering rain on rain-free images. This paper proposes to realize continuous control of rain intensity bidirectionally, from clear rain-free to downpour image with a single rain image as input, without changing th…
In this paper, we explore the compression of deep neural networks by quantizing the weights and activations into multi-bit binary networks (MBNs). A distribution-aware multi-bit quantization (DMBQ) method that incorporates the distribution prior into the optimization of quantization is proposed. Ins…
Light field images contain both angular and spatial information of captured light rays. The rich information of light fields enables straightforward disparity recovery capability but demands high computational cost as well. In this paper, we design a lightweight disparity estimation model with physi…
Enhancing low light videos, which consists of denoising and brightness adjustment, is an intriguing but knotty problem. Under low light condition, due to high sensitivity camera setting, commonly negligible noises become obvious and severely deteriorate the captured videos. To recover high quality v…
Hyperspectral images can provide rich clues for various computer vision tasks. However, the requirements of professional and expensive hardware for capturing hyperspectral images impede its wide applications. In this paper, based on a simple but not widely noticed phenomenon that the color printer c…
Developing high light efficiency imaging techniques to retrieve high dimensional optical signal is a long-term goal in computational photography. Multispectral imaging, which captures images of different wavelengths and boosting the abilities for revealing scene properties, has developed rapidly in…
Light fields have many applications in machine vision, consumer photography, robotics, and microscopy. However, the prevalent resolution limits of existing light field imaging systems hinder widespread adoption. In this paper, we analyze fundamental resolution limits of light field cameras in the di…