Search Results for author: Yulia Gryaditskaya

Found 10 papers, 6 papers with code

Open Vocabulary Semantic Scene Sketch Understanding

no code implementations18 Dec 2023 Ahmed Bourouis, Judith Ellen Fan, Yulia Gryaditskaya

To obtain generalization to a large set of sketches and categories, we build on a vision transformer encoder pretrained with the CLIP model.

Disentanglement Visual Prompt Tuning

Fine-Tuned but Zero-Shot 3D Shape Sketch View Similarity and Retrieval

no code implementations14 Jun 2023 Gianluca Berardi, Yulia Gryaditskaya

We believe that our work will have a significant impact on research in the sketch domain, providing insights and guidance on how to adopt large pretrained models as perceptual losses.

Contrastive Learning Retrieval

SketchXAI: A First Look at Explainability for Human Sketches

no code implementations CVPR 2023 Zhiyu Qu, Yulia Gryaditskaya, Ke Li, Kaiyue Pang, Tao Xiang, Yi-Zhe Song

Following this, we design a simple explainability-friendly sketch encoder that accommodates the intrinsic properties of strokes: shape, location, and order.

Explainable artificial intelligence Explainable Artificial Intelligence (XAI) +1

Towards 3D VR-Sketch to 3D Shape Retrieval

1 code implementation20 Sep 2022 Ling Luo, Yulia Gryaditskaya, Yongxin Yang, Tao Xiang, Yi-Zhe Song

In this paper, we offer a different perspective towards answering these questions -- we study the use of 3D sketches as an input modality and advocate a VR-scenario where retrieval is conducted.

3D Shape Retrieval Retrieval

Fine-Grained VR Sketching: Dataset and Insights

1 code implementation20 Sep 2022 Ling Luo, Yulia Gryaditskaya, Yongxin Yang, Tao Xiang, Yi-Zhe Song

We then, for the first time, study the scenario of fine-grained 3D VR sketch to 3D shape retrieval, as a novel VR sketching application and a proving ground to drive out generic insights to inform future research.

3D Shape Reconstruction 3D Shape Retrieval +1

Structure-Aware 3D VR Sketch to 3D Shape Retrieval

1 code implementation19 Sep 2022 Ling Luo, Yulia Gryaditskaya, Tao Xiang, Yi-Zhe Song

In particular, we propose to use a triplet loss with an adaptive margin value driven by a "fitting gap", which is the similarity of two shapes under structure-preserving deformations.

3D Shape Retrieval Retrieval

One Sketch for All: One-Shot Personalized Sketch Segmentation

no code implementations20 Dec 2021 Anran Qi, Yulia Gryaditskaya, Tao Xiang, Yi-Zhe Song

We aim to segment all sketches belonging to the same category provisioned with a single sketch with a given part annotation while (i) preserving the parts semantics embedded in the exemplar, and (ii) being robust to input style and abstraction.

Segmentation

Deep Sketch-Based Modeling: Tips and Tricks

1 code implementation12 Nov 2020 Yue Zhong, Yulia Gryaditskaya, Honggang Zhang, Yi-Zhe Song

Deep image-based modeling received lots of attention in recent years, yet the parallel problem of sketch-based modeling has only been briefly studied, often as a potential application.

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