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How do we infer a 3D scene from a single image in the presence of corruptions like rain, snow or fog? Straightforward domain randomization relies on knowing the family of corruptions ahead of time. Here, we propose a Bayesian…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Tuan Anh Le , Pavel Sountsov , Matthew D. Hoffman , Ben Lee , Brian Patton , Rif A. Saurous

This paper proposes a practical photometric solution for the challenging problem of in-the-wild inverse rendering under unknown ambient lighting. Our system recovers scene geometry and reflectance using only multi-view images captured by a…

Computer Vision and Pattern Recognition · Computer Science 2023-03-27 Ziang Cheng , Junxuan Li , Hongdong Li

In light of the rising demand for biometric-authentication systems, preventing face spoofing attacks is a critical issue for the safe deployment of face recognition systems. Here, we propose an efficient face presentation attack detection…

Computer Vision and Pattern Recognition · Computer Science 2020-12-17 Akinori F. Ebihara , Kazuyuki Sakurai , Hitoshi Imaoka

Neural Radiance Fields (NeRF) have demonstrated exceptional capabilities in reconstructing complex scenes with high fidelity. However, NeRF's view dependency can only handle low-frequency reflections. It falls short when handling complex…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Chen Gao , Yipeng Wang , Changil Kim , Jia-Bin Huang , Johannes Kopf

Flash is an essential tool as it often serves as the sole controllable light source in everyday photography. However, the use of flash is a binary decision at the time a photograph is captured with limited control over its characteristics…

Computer Vision and Pattern Recognition · Computer Science 2023-06-12 Sepideh Sarajian Maralan , Chris Careaga , Yağız Aksoy

State-of-the-art techniques for 3D reconstruction are largely based on volumetric scene representations, which require sampling multiple points to compute the color arriving along a ray. Using these representations for more general inverse…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Benjamin Attal , Dor Verbin , Ben Mildenhall , Peter Hedman , Jonathan T. Barron , Matthew O'Toole , Pratul P. Srinivasan

Wireless communication using fully passive metal reflectors is a promising technique for coverage expansion, signal enhancement, rank improvement and blind-zone compensation, thanks to its appealing features including zero energy…

Information Theory · Computer Science 2022-11-17 Zhi Yu , Chao Feng , Yong Zeng , Teng Li , Shi Jin

Scene inference under low-light is a challenging problem due to severe noise in the captured images. One way to reduce noise is to use longer exposure during the capture. However, in the presence of motion (scene or camera motion), longer…

Computer Vision and Pattern Recognition · Computer Science 2022-07-26 Bhavya Goyal , Jean-François Lalonde , Yin Li , Mohit Gupta

How to make a material anti-reflective without changing its high refraction index? Achieving anti-reflection in high-refractive-index materials poses challenges due to their high reflectivity (Fresnel equations). Based on theory with new…

Optics · Physics 2024-08-12 V. Gareyan , N. Margaryan , Zh. Gevorkian

Removing undesired reflections from a photo taken in front of glass is of great importance for enhancing visual computing systems' efficiency. Previous learning-based approaches have produced visually plausible results for some reflections…

Image and Video Processing · Electrical Eng. & Systems 2021-03-31 Sutanu Bera , Prabir Kumar Biswas

Intrinsic image decomposition aims to separate the surface reflectance and the effects from the illumination given a single photograph. Due to the complexity of the problem, most prior works assume a single-color illumination and a…

Computer Vision and Pattern Recognition · Computer Science 2024-09-23 Chris Careaga , Yağız Aksoy

We present a method to separate a single image captured under two illuminants, with different spectra, into the two images corresponding to the appearance of the scene under each individual illuminant. We do this by training a deep neural…

Computer Vision and Pattern Recognition · Computer Science 2019-04-24 Zhuo Hui , Ayan Chakrabarti , Kalyan Sunkavalli , Aswin C. Sankaranarayanan

Empowered by deep learning, recent methods for material capture can estimate a spatially-varying reflectance from a single photograph. Such lightweight capture is in stark contrast with the tens or hundreds of pictures required by…

Graphics · Computer Science 2019-06-28 Valentin Deschaintre , Miika Aittala , Fredo Durand , George Drettakis , Adrien Bousseau

We present a simple but effective method to extract the reflectivity spectra from the interference signals with a large NA white light interferometry. Numerical simulations and experiments have demonstrated the effectiveness of our method.…

Optics · Physics 2025-03-11 Cheng Chen , Lixuan Xu , Rong Su

Flatbed scanners have emerged as promising devices for high-resolution, single-image material capture. However, existing approaches assume very specific conditions, such as uniform diffuse illumination, which are only available in certain…

Neural radiance fields (NeRF) have revolutionized the field of image-based view synthesis. However, NeRF uses straight rays and fails to deal with complicated light path changes caused by refraction and reflection. This prevents NeRF from…

Computer Vision and Pattern Recognition · Computer Science 2023-09-25 Xiaoxue Chen , Junchen Liu , Hao Zhao , Guyue Zhou , Ya-Qin Zhang

Reflection phase imaging provides label-free, high-resolution characterization of biological samples, typically using interferometric-based techniques. Here, we investigate reflection phase microscopy from intensity-only measurements under…

Quantitative Methods · Quantitative Biology 2019-12-18 Alex Matlock , Anne Sentenac , Patrick C. Chaumet , Ji Yi , Lei Tian

Ray tracing is widely employed to model the propagation of radio-frequency (RF) signal in complex environment. The modelling performance greatly depends on how accurately the target scene can be depicted, including the scene geometry and…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Haifeng Jia , Xinyi Chen , Yichen Wei , Yifei Sun , Yibo Pi

Photography usually requires optics in conjunction with a recording device (an image sensor). Eliminating the optics could lead to new form factors for cameras. Here, we report a simple demonstration of imaging using a bare CMOS sensor that…

Computer Vision and Pattern Recognition · Computer Science 2018-05-23 Ganghun Kim , Kyle Isaacson , Racheal Palmer , Rajesh Menon

This paper proposes a non-computational method of counteracting the effect of image degradation introduced by the diffraction phenomenon in lensless microscopy. All the optical images (whether focused by lenses or not) are diffraction…

Optics · Physics 2021-04-08 Sanjeev Kumar , Manjunatha Mahadevappa , Pranab Kumar Dutta