1 citations · 3 across the 10 of their papers we have counts for
13 papers
BeyondMasks: Evaluating Causal and Physical Consistency in Video Object Removal
Yigit Ekin, Enes Sanli, Aykut Erdem +2
Recent advances in generative video models have significantly improved visual realism in video object removal, yet evaluation protocols still focus on masked region fidelity, treat…
RoPEMover: Depth-Aware Object Relocation via Positional Embeddings
Ipek Oztas, Duygu Ceylan, Aybars Bugra Aksoy +1
Moving an object in a single image requires geometry-consistent spatial rearrangement, including handling occlusions, revealing previously unseen regions, and maintaining coherent…
FullCircle: Effortless 3D Reconstruction from Casual 360 Captures
Yalda Foroutan, Ipek Oztas, Daniel Rebain +4
Radiance fields have emerged as powerful tools for 3D scene reconstruction. However, casual capture remains challenging due to the narrow field of view of perspective cameras, whic…
GeoFusionLRM: Geometry-Aware Self-Correction for Consistent 3D Reconstruction
Ahmet Burak Yildirim, Tuna Saygin, Duygu Ceylan +1
Single-image 3D reconstruction with large reconstruction models (LRMs) has advanced rapidly, yet reconstructions often exhibit geometric inconsistencies and misaligned details that…
StyleFusion360: View-Consistent Head Stylization via Adaptive Style Modulation
Furkan Guzelant, Arda Goktogan, Tarık Kaya +1
3D head stylization enables expressive reimagining of human faces for creative visual experiences in digital media. Existing 3D-aware methods often require computationally intensiv…
RoPECraft: Training-Free Motion Transfer with Trajectory-Guided RoPE Optimization on Diffusion Transformers
Ahmet Berke Gokmen, Yigit Ekin, Bahri Batuhan Bilecen +1
We propose RoPECraft, a training-free video motion transfer method for diffusion transformers that operates solely by modifying their rotary positional embeddings (RoPE). We first…
3D Stylization via Large Reconstruction Model
Ipek Oztas, Duygu Ceylan, Aysegul Dundar
With the growing success of text or image guided 3D generators, users demand more control over the generation process, appearance stylization being one of them. Given a reference i…
MD-ProjTex: Texturing 3D Shapes with Multi-Diffusion Projection
Ahmet Burak Yildirim, Mustafa Utku Aydogdu, Duygu Ceylan +1
We introduce MD-ProjTex, a method for fast and consistent text-guided texture generation for 3D shapes using pretrained text-to-image diffusion models. At the core of our approach…
Identity Preserving 3D Head Stylization with Multiview Score Distillation
Bahri Batuhan Bilecen, Ahmet Berke Gokmen, Furkan Guzelant +1
3D head stylization transforms realistic facial features into artistic representations, enhancing user engagement across gaming and virtual reality applications. While 3D-aware gen…
Dual Encoder GAN Inversion for High-Fidelity 3D Head Reconstruction from Single Images
Bahri Batuhan Bilecen, Ahmet Berke Gokmen, Aysegul Dundar
3D GAN inversion aims to project a single image into the latent space of a 3D Generative Adversarial Network (GAN), thereby achieving 3D geometry reconstruction. While there exist…
CLIPAway: Harmonizing Focused Embeddings for Removing Objects via Diffusion Models
Yigit Ekin, Ahmet Burak Yildirim, Erdem Eren Caglar +3
Advanced image editing techniques, particularly inpainting, are essential for seamlessly removing unwanted elements while preserving visual integrity. Traditional GAN-based methods…
Reference-Based 3D-Aware Image Editing with Triplanes
Bahri Batuhan Bilecen, Yigit Yalin, Ning Yu +1
Generative Adversarial Networks (GANs) have emerged as powerful tools for high-quality image generation and real image editing by manipulating their latent spaces. Recent advanceme…
Warping the Residuals for Image Editing with StyleGAN
Ahmet Burak Yildirim, Hamza Pehlivan, Aysegul Dundar
StyleGAN models show editing capabilities via their semantically interpretable latent organizations which require successful GAN inversion methods to edit real images. Many works h…