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  1. Creating thematic collections in industries demands innovative designs and cohesive concepts. Designers may face challenges in maintaining thematic consistency when drawing inspiration from existing objects, landscapes, or artifacts. While AI-powered graphic design tools offer help, they often fail to generate cohesive sets based on specific thematic concepts. In response, we introduce iCONTRA, an interactive CONcept TRAnsfer system. With a user-friendly interface, iCONTRA enables both experienced designers and novices to effortlessly explore creative design concepts and efficiently generate thematic collections. We also propose a zero-shot image editing algorithm, eliminating the need for fine-tuning models, which gradually integrates information from initial objects, ensuring consistency in the generation process without influencing the background. A pilot study suggests iCONTRA’s potential to reduce designers’ efforts. Experimental results demonstrate its effectiveness in producing consistent and high-quality object concept transfers. iCONTRA stands as a promising tool for innovation and creative exploration in thematic collection design. 
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    Free, publicly-accessible full text available May 2, 2025
  2. Drawing is an art that enables people to express their imagination and emotions. However, individuals usually face challenges in drawing, especially when translating conceptual ideas into visually coherent representations and bridging the gap between mental visualization and practical execution. In response, we propose ARtVista - a novel system integrating AR and generative AI technologies. ARtVista not only recommends reference images aligned with users’ abstract ideas and generates sketches for users to draw but also goes beyond, crafting vibrant paintings in various painting styles. ARtVista also offers users an alternative approach to create striking paintings by simulating the paint-by-number concept on reference images, empowering users to create visually stunning artwork devoid of the necessity for advanced drawing skills. We perform a pilot study and reveal positive feedback on its usability, emphasizing its effectiveness in visualizing user ideas and aiding the painting process to achieve stunning pictures without requiring advanced drawing skills. 
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    Free, publicly-accessible full text available May 11, 2025
  3. Few-shot instance segmentation extends the few-shot learning paradigm to the instance segmentation task, which tries to segment instance objects from a query image with a few annotated examples of novel categories. Conventional approaches have attempted to address the task via prototype learning, known as point estimation. However, this mechanism depends on prototypes (e.g. mean of K-shot) for prediction, leading to performance instability. To overcome the disadvantage of the point estimation mechanism, we propose a novel approach, dubbed MaskDiff, which models the underlying conditional distribution of a binary mask, which is conditioned on an object region and K-shot information. Inspired by augmentation approaches that perturb data with Gaussian noise for populating low data density regions, we model the mask distribution with a diffusion probabilistic model. We also propose to utilize classifier-free guided mask sampling to integrate category information into the binary mask generation process. Without bells and whistles, our proposed method consistently outperforms state-of-the-art methods on both base and novel classes of the COCO dataset while simultaneously being more stable than existing methods. The source code is available at: https://github.com/minhquanlecs/MaskDiff. 
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    Free, publicly-accessible full text available March 25, 2025
  4. Public speaking is one of the most important ways to share ideas with many people in different domains such as education, training, marketing, or healthcare. Being able to master this skill allows the speaker to clearly advocate for their subject and greatly influence others. However, most of the population reported having public speaking anxiety or glossophobia, which prevents them from effectively conveying their messages to others. One of the best solutions is to have a safe and private space to practice speaking in front of others. As a result, this research work is proposed with the overarching goal of providing people with virtual environments to practice in front of simulated audiences. In addition, the proposed work will aim to have live audience feedback and speech analysis details which could be useful for the users. The experiments via a user study provide insights into the proposed public speaking simulator. 
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  5. In developing countries, high schoolers rarely have opportunities to conduct chemical experiments due to the lack of facilities. There-fore, chemistry experiment simulation is an alternative environment for students to do the chemistry lab assignments. Despite the need of creating virtual simulations to expand the application usability, it is challenging to synthesize a realistic environment given the limited computing resources. In this paper, we propose Chemisim, a highly realistic web-based VR laboratory simulation for students with high quality and usability. In particular, we make use of the fluid simulation system to mimic real chemical reactions. The imple-mented simulation was based on the chemistry assignments in the national education system, consulted by chemical teachers. Then we deployed the simulator on the web to promote a wide range of students usage. The system was evaluated by collecting and analyzing feedback from chemical teachers based on four criteria, namely, convenience, realism, functionality, and preferences. Our experimental findings address educational challenges and produce innovative technical solutions to solve them in developing countries. 
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