168 citations · 177 across the 6 of their papers we have counts for
9 papers
iEdit: Localised Text-guided Image Editing with Weak Supervision
Rumeysa Bodur, Erhan Gundogdu, Binod Bhattarai +3
Diffusion models (DMs) can generate realistic images with text guidance using large-scale datasets. However, they demonstrate limited controllability in the output space of the gen…
Contrastive Language-Action Pre-training for Temporal Localization
Mengmeng Xu, Erhan Gundogdu, Maksim Lapin +3
Long-form video understanding requires designing approaches that are able to temporally localize activities or language. End-to-end training for such tasks is limited by the comput…
ABO: Dataset and Benchmarks for Real-World 3D Object Understanding
Jasmine Collins, Shubham Goel, Kenan Deng +9
We introduce Amazon Berkeley Objects (ABO), a new large-scale dataset designed to help bridge the gap between real and virtual 3D worlds. ABO contains product catalog images, metad…
Revamping Cross-Modal Recipe Retrieval with Hierarchical Transformers and Self-supervised Learning
Amaia Salvador, Erhan Gundogdu, Loris Bazzani +1
Cross-modal recipe retrieval has recently gained substantial attention due to the importance of food in people's lives, as well as the availability of vast amounts of digital cooki…
GarNet++: Improving Fast and Accurate Static3D Cloth Draping by Curvature Loss
Erhan Gundogdu, Victor Constantin, Shaifali Parashar +4
In this paper, we tackle the problem of static 3D cloth draping on virtual human bodies. We introduce a two-stream deep network model that produces a visually plausible draping of…
Shape Reconstruction by Learning Differentiable Surface Representations
Jan Bednarik, Shaifali Parashar, Erhan Gundogdu +2
Generative models that produce point clouds have emerged as a powerful tool to represent 3D surfaces, and the best current ones rely on learning an ensemble of parametric represent…
Quadruplet Selection Methods for Deep Embedding Learning
Kaan Karaman, Erhan Gundogdu, Aykut Koc +1
Recognition of objects with subtle differences has been used in many practical applications, such as car model recognition and maritime vessel identification. For discrimination of…
GarNet: A Two-Stream Network for Fast and Accurate 3D Cloth Draping
Erhan Gundogdu, Victor Constantin, Amrollah Seifoddini +3
While Physics-Based Simulation (PBS) can accurately drape a 3D garment on a 3D body, it remains too costly for real-time applications, such as virtual try-on. By contrast, inferenc…
Good Features to Correlate for Visual Tracking
Erhan Gundogdu, A. Aydin Alatan
During the recent years, correlation filters have shown dominant and spectacular results for visual object tracking. The types of the features that are employed in these family of…