88 citations · 110 across the 6 of their papers we have counts for
8 papers
S2F2: Self-Supervised High Fidelity Face Reconstruction from Monocular Image
Abdallah Dib, Junghyun Ahn, Cedric Thebault +2
We present a novel face reconstruction method capable of reconstructing detailed face geometry, spatially varying face reflectance from a single monocular image. We build our work…
Towards High Fidelity Monocular Face Reconstruction with Rich Reflectance using Self-supervised Learning and Ray Tracing
Abdallah Dib, Cedric Thebault, Junghyun Ahn +3
Robust face reconstruction from monocular image in general lighting conditions is challenging. Methods combining deep neural network encoders with differentiable rendering have ope…
PhotoApp: Photorealistic Appearance Editing of Head Portraits
Mallikarjun B R, Ayush Tewari, Abdallah Dib +8
Photorealistic editing of portraits is a challenging task as humans are very sensitive to inconsistencies in faces. We present an approach for high-quality intuitive editing of the…
Practical Face Reconstruction via Differentiable Ray Tracing
Abdallah Dib, Gaurav Bharaj, Junghyun Ahn +4
We present a differentiable ray-tracing based novel face reconstruction approach where scene attributes - 3D geometry, reflectance (diffuse, specular and roughness), pose, camera p…
Face Reflectance and Geometry Modeling via Differentiable Ray Tracing
Abdallah Dib, Gaurav Bharaj, Junghyun Ahn +3
We present a novel strategy to automatically reconstruct 3D faces from monocular images with explicitly disentangled facial geometry (pose, identity and expression), reflectance (d…
SoDeep: a Sorting Deep net to learn ranking loss surrogates
Martin Engilberge, Louis Chevallier, Patrick Pérez +1
Several tasks in machine learning are evaluated using non-differentiable metrics such as mean average precision or Spearman correlation. However, their non-differentiability preven…
Finding beans in burgers: Deep semantic-visual embedding with localization
Martin Engilberge, Louis Chevallier, Patrick Pérez +1
Several works have proposed to learn a two-path neural network that maps images and texts, respectively, to a same shared Euclidean space where geometry captures useful semantic re…
Hybrid multi-layer Deep CNN/Aggregator feature for image classification
Praveen Kulkarni, Joaquin Zepeda, Frederic Jurie +2
Deep Convolutional Neural Networks (DCNN) have established a remarkable performance benchmark in the field of image classification, displacing classical approaches based on hand-ta…