activity
20182022
most citedPIE-Net: Photometric Invariant Edge Guided Network for Intrinsic Image Decomposition

3 citations · 4 across the 2 of their papers we have counts for

collaborators
Showing cs.CVShow all

7 papers · 1 filter

cs.CV20223 cited

PIE-Net: Photometric Invariant Edge Guided Network for Intrinsic Image Decomposition

Partha Das, Sezer Karaoglu, Theo Gevers

Intrinsic image decomposition is the process of recovering the image formation components (reflectance and shading) from an image. Previous methods employ either explicit priors to…

cs.CV2021

Generative Models for Multi-Illumination Color Constancy

Partha Das, Yang Liu, Sezer Karaoglu +1

In this paper, the aim is multi-illumination color constancy. However, most of the existing color constancy methods are designed for single light sources. Furthermore, datasets for…

cs.CV20201 cited

EDEN: Multimodal Synthetic Dataset of Enclosed GarDEN Scenes

Hoang-An Le, Thomas Mensink, Partha Das +2

Multimodal large-scale datasets for outdoor scenes are mostly designed for urban driving problems. The scenes are highly structured and semantically different from scenarios seen i…

cs.CV2020

Novel View Synthesis from Single Images via Point Cloud Transformation

Hoang-An Le, Thomas Mensink, Partha Das +1

In this paper the argument is made that for true novel view synthesis of objects, where the object can be synthesized from any viewpoint, an explicit 3D shape representation isdesi…

cs.CV2019

ShadingNet: Image Intrinsics by Fine-Grained Shading Decomposition

Anil S. Baslamisli, Partha Das, Hoang-An Le +2

In general, intrinsic image decomposition algorithms interpret shading as one unified component including all photometric effects. As shading transitions are generally smoother tha…

cs.CV2018

Color Constancy by GANs: An Experimental Survey

Partha Das, Anil S. Baslamisli, Yang Liu +2

In this paper, we formulate the color constancy task as an image-to-image translation problem using GANs. By conducting a large set of experiments on different datasets, an experim…