activity
20182024
most citedEditing in Style: Uncovering the Local Semantics of GANs

9 citations · 22 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2024★ 4 cited

InseRF: Text-Driven Generative Object Insertion in Neural 3D Scenes

Mohamad Shahbazi, Liesbeth Claessens, Michael Niemeyer +4

We introduce InseRF, a novel method for generative object insertion in the NeRF reconstructions of 3D scenes. Based on a user-provided textual description and a 2D bounding box in…

cs.CV2023

NeRF-GAN Distillation for Efficient 3D-Aware Generation with Convolutions

Mohamad Shahbazi, Evangelos Ntavelis, Alessio Tonioni +4

Pose-conditioned convolutional generative models struggle with high-quality 3D-consistent image generation from single-view datasets, due to their lack of sufficient 3D priors. Rec…

cs.CV2020★ 9 cited

Editing in Style: Uncovering the Local Semantics of GANs

Edo Collins, Raja Bala, Bob Price +1

While the quality of GAN image synthesis has improved tremendously in recent years, our ability to control and condition the output is still limited. Focusing on StyleGAN, we intro…

cs.LG2018★ 3 cited

Detecting Memorization in ReLU Networks

Edo Collins, Siavash Arjomand Bigdeli, Sabine Süsstrunk

We propose a new notion of `non-linearity' of a network layer with respect to an input batch that is based on its proximity to a linear system, which is reflected in the non-negati…

cs.LG2018★ 6 cited

Deep Feature Factorization For Concept Discovery

Edo Collins, Radhakrishna Achanta, Sabine Süsstrunk

We propose Deep Feature Factorization (DFF), a method capable of localizing similar semantic concepts within an image or a set of images. We use DFF to gain insight into a deep con…