activity
20162023
most citedRain rendering for evaluating and improving robustness to bad weather

119 citations · 195 across the 20 of their papers we have counts for

collaborators

39 papers

eess.IV2023

Domain Agnostic Image-to-image Translation using Low-Resolution Conditioning

Mohamed Abid, Arman Afrasiyabi, Ihsen Hedhli +2

Generally, image-to-image translation (i2i) methods aim at learning mappings across domains with the assumption that the images used for translation share content (e.g., pose) but…

cs.CV2023★ 4 cited

EverLight: Indoor-Outdoor Editable HDR Lighting Estimation

Mohammad Reza Karimi Dastjerdi, Jonathan Eisenmann, Yannick Hold-Geoffroy +1

Because of the diversity in lighting environments, existing illumination estimation techniques have been designed explicitly on indoor or outdoor environments. Methods have focused…

cs.CV2023★ 2 cited

Beyond the Pixel: a Photometrically Calibrated HDR Dataset for Luminance and Color Prediction

Christophe Bolduc, Justine Giroux, Marc Hébert +2

Light plays an important role in human well-being. However, most computer vision tasks treat pixels without considering their relationship to physical luminance. To address this sh…

cs.CV2023

DarSwin: Distortion Aware Radial Swin Transformer

Akshaya Athwale, Arman Afrasiyabi, Justin Lagüe +3

Wide-angle lenses are commonly used in perception tasks requiring a large field of view. Unfortunately, these lenses produce significant distortions, making conventional models tha…

cs.CV2023★ 1 cited

Robust Unsupervised StyleGAN Image Restoration

Yohan Poirier-Ginter, Jean-François Lalonde

GAN-based image restoration inverts the generative process to repair images corrupted by known degradations. Existing unsupervised methods must be carefully tuned for each task and…

cs.GR2023★ 1 cited

LM-GAN: A Photorealistic All-Weather Parametric Sky Model

Lucas Valença, Ian Maquignaz, Hadi Moazen +3

We present LM-GAN, an HDR sky model that generates photorealistic environment maps with weathered skies. Our sky model retains the flexibility of traditional parametric models and…