3 citations · 4 across the 14 of their papers we have counts for
15 papers
LeRF: Learning Reference Coordinate Frames for Perspective Taking Reasoning
Bang Xiao, Wenqi Jia, Ozgur Kara +5
Perspective taking is a fundamental component of spatial intelligence, requiring models interpret spatial relations from a specified viewpoint, such as that of another entity or an…
ConvDeck: Conversational Paper-to-Slide Generation via Stage-Specific User Feedback
Tarik Can Ozden, Sachidanand VS, Furkan Horoz +4
Automatic academic paper-to-slide generation is inherently iterative, because creating an effective presentation requires repeated cycles of generation, critique, and revision. Rec…
A Survey on Adversarial Attacks and Defenses for Diffusion Models Across Multiple Modalities
Ozgur Kara, Tarik Can Ozden, Furkan Horoz +6
Diffusion models have become the dominant family of generative models in the visual domain. However, their widespread public availability enables misuse at scale, motivating a rapi…
Exact Posterior Score Estimation for Solving Linear Inverse Problems
Abbas Mammadov, Ozgur Kara, Kaan Oktay +5
Diffusion and flow-based models learn powerful data priors by training a denoiser to reverse Gaussian corruption. To use this prior to solve a linear inverse problem, one needs to…
ST-DiffEye: Diffusion-based Continuous Gaze Generation via Joint Scanpath-Trajectory Modeling
Brian Nlong Zhao, Ozgur Kara, Junho Kim +1
We study the problem of human gaze modeling, which aims to generate the gaze patterns a viewer produces while observing a visual stimulus. Gaze is primarily captured through two mo…
Narrative-Driven Paper-to-Slide Generation via ArcDeck
Tarik Can Ozden, Sachidanand VS, Furkan Horoz +3
We introduce ArcDeck, a multi-agent framework that formulates paper-to-slide generation as a structured narrative reconstruction task. Unlike existing methods that directly summari…
Immune2V: Image Immunization Against Dual-Stream Image-to-Video Generation
Zeqian Long, Ozgur Kara, Haotian Xue +2
Image-to-video (I2V) generation has the potential for societal harm because it enables the unauthorized animation of static images to create realistic deepfakes. While existing def…
Layer-Aware Video Composition via Split-then-Merge
Ozgur Kara, Yujia Chen, Ming-Hsuan Yang +3
We present Split-then-Merge (StM), a novel framework designed to enhance control in generative video composition and address its data scarcity problem. Unlike conventional methods…
DiffEye: Diffusion-Based Continuous Eye-Tracking Data Generation Conditioned on Natural Images
Ozgur Kara, Harris Nisar, James M. Rehg
Numerous models have been developed for scanpath and saliency prediction, which are typically trained on scanpaths, which model eye movement as a sequence of discrete fixation poin…
ShotAdapter: Text-to-Multi-Shot Video Generation with Diffusion Models
Ozgur Kara, Krishna Kumar Singh, Feng Liu +3
Current diffusion-based text-to-video methods are limited to producing short video clips of a single shot and lack the capability to generate multi-shot videos with discrete transi…
DiffVax: Optimization-Free Image Immunization Against Diffusion-Based Editing
Tarik Can Ozden, Ozgur Kara, Oguzhan Akcin +4
Current image immunization defense techniques against diffusion-based editing embed imperceptible noise into target images to disrupt editing models. However, these methods face sc…
Towards Social AI: A Survey on Understanding Social Interactions
Sangmin Lee, Minzhi Li, Bolin Lai +8
Social interactions form the foundation of human societies. Artificial intelligence has made significant progress in certain areas, but enabling machines to seamlessly understand s…
Leveraging Object Priors for Point Tracking
Bikram Boote, Anh Thai, Wenqi Jia +4
Point tracking is a fundamental problem in computer vision with numerous applications in AR and robotics. A common failure mode in long-term point tracking occurs when the predicte…
Transfer Learning for Cross-dataset Isolated Sign Language Recognition in Under-Resourced Datasets
Ahmet Alp Kindiroglu, Ozgur Kara, Ogulcan Ozdemir +1
Sign language recognition (SLR) has recently achieved a breakthrough in performance thanks to deep neural networks trained on large annotated sign datasets. Of the many different s…
RAVE: Randomized Noise Shuffling for Fast and Consistent Video Editing with Diffusion Models
Ozgur Kara, Bariscan Kurtkaya, Hidir Yesiltepe +2
Recent advancements in diffusion-based models have demonstrated significant success in generating images from text. However, video editing models have not yet reached the same leve…