2 citations · 5 across the 6 of their papers we have counts for
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Geo-ID: Test-Time Geometric Consensus for Cross-View Consistent Intrinsics
Alara Dirik, Stefanos Zafeiriou
Intrinsic image decomposition aims to estimate physically based rendering (PBR) parameters such as albedo, roughness, and metallicity from images. While recent methods achieve stro…
ReasonX: MLLM-Guided Intrinsic Image Decomposition
Alara Dirik, Tuanfeng Wang, Duygu Ceylan +2
Intrinsic image decomposition aims to separate images into physical components such as albedo, depth, normals, and illumination. While recent diffusion- and transformer-based model…
3D-LatentMapper: View Agnostic Single-View Reconstruction of 3D Shapes
Alara Dirik, Pinar Yanardag
Computer graphics, 3D computer vision and robotics communities have produced multiple approaches to represent and generate 3D shapes, as well as a vast number of use cases. However…
XDGAN: Multi-Modal 3D Shape Generation in 2D Space
Hassan Abu Alhaija, Alara Dirik, André Knörig +2
Generative models for 2D images has recently seen tremendous progress in quality, resolution and speed as a result of the efficiency of 2D convolutional architectures. However it i…
FairStyle: Debiasing StyleGAN2 with Style Channel Manipulations
Cemre Karakas, Alara Dirik, Eylul Yalcinkaya +1
Recent advances in generative adversarial networks have shown that it is possible to generate high-resolution and hyperrealistic images. However, the images produced by GANs are on…
Text and Image Guided 3D Avatar Generation and Manipulation
Zehranaz Canfes, M. Furkan Atasoy, Alara Dirik +1
The manipulation of latent space has recently become an interesting topic in the field of generative models. Recent research shows that latent directions can be used to manipulate…