We present CoStage, an AI-supported embodied co-creation platform that combines LLM-based story generation with multi-robot stage performance to support children’s narrative construction and spatial imagination. Unlike prior AI storytelling tools that are largely screen-based, CoStage allows children to direct robot actors on a 360° tangible stage, transforming written stories into spatially enacted performances. Informed by formative work with domain experts, we evaluated CoStage in a within-subjects study (N = 24) comparing a robot enactment condition with a screen-based animation condition. Our findings indicate that robot-stage performance can heighten immersion, strengthen children’s sense of directorial agency, support spatial sensemaking, and foster a planning–enactment coordination loop during storytelling. This work advances child–computer interaction by offering design implications and demonstrating how embodied AI co-creation can support children’s spatial cognition and narrative engagement.

Digital platforms frequently reproduce heteronormative norms and structural biases, limiting inclusive communication between LGBTQ+ and cisgender individuals. The Metaverse, with its affordances for identity fluidity, presence, and community governance, offers a promising site for reimagining such interactions. To investigate this potential, we conducted participatory design workshops involving LGBTQ+ and cisgender participants, situating them in speculative Metaverse contexts to surface barriers and co-create alternative futures. The workshops followed a three-phase process—identifying challenges, speculative problem-solving, and visualizing futures—yielding socio-spatial-technical solutions across four layers: embodied interaction, negotiated visibility, community formation, and reconfigured norms. These findings highlight the importance of spatial cues and power dynamics in shaping digital encounters. We contribute by (1) articulating challenges of cross-group communication in virtual environments, (2) proposing inclusive design opportunities for the Metaverse, and (3) advancing principles for addressing power geometry in digital space. This work demonstrates futuring as a critical strategy for designing equitable, transformative communication infrastructures.

The Kaiping Diaolou and Villages, a UNESCO World Heritage Site, exemplify hybrid Chinese and Western architecture shaped by migration culture. However, architectural heritage engagement often faces authenticity debates, resource constraints, and limited participatory approaches. This research explores current challenges of leveraging Artificial Intelligence (AI) for architectural heritage, and how AI-assisted interactive systems can foster cultural heritage understanding and preservation awareness. We conducted a formative study (N=14) to uncover empirical insights from heritage stakeholders that inform design. These insights informed the design of Gen-Diaolou, an integrated AI-assisted interactive system that supports heritage understanding and preservation. A pilot study (N=18) and a museum field study (N=26) provided converging evidence suggesting that Gen-Diaolou may support visitors’ diachronic understanding and preservation awareness, and together informed design implications for future human–AI collaborative systems for digital cultural heritage engagement. More broadly, this work bridges the research gap between passive heritage systems and unconstrained creative tools in the HCI domain.

Photo-based reminiscence can support well-being in older adults, yet most systems remain text-driven and offer little real-time adaptivity. We first conduct expert interviews to derive design considerations for accessibility, cultural fit, and safe emotional engagement. We then implemented Eye2Recall, an intelligent conversational interface that converts users’ gazes on old photos into mixed-initiative prompts for a large language model (LLM). We evaluated it in a pilot study with 12 older adults. Participants reported low-effort, smooth interactions, and perceived the agent’s questions as aligned with what they were looking at. Immediately after use, self-reported positive mood increased and negative mood decreased. Interviews further indicated that gaze-driven prompts helped retrieve concrete details and supported reflective storytelling. Our contribution is a concrete mechanism for gaze-to-prompt adaptivity that operationalizes mixed-initiative dialogue for older adults’ reminiscence experience.

This paper presents The Woven Atlas, an immersive interactive installation that examines the potential for connectivity in interactive art and immersive media within the context of the Silk Road. The artwork encourages collective participation among on-site participants, enabling the audience to influence the presentation of history through their involvement with the multimedia system. To enhance real-time performance, we have developed a program using C++ and OpenGL to support the artwork. The customized program integrates a set of large-screen displays and LiDAR systems, providing the audience with an immersive interactive and cultural experience. The Woven Atlas reinforces the interconnected role of Silk Road cultures through interactive technologies and real-time multimedia systems. It allows audiences to explore the process of experiencing culture and history through multi-person participation and real-time graphics.

This paper presents Viu, a project that transforms the visual beauty of traditional textile art of the Li ethnic minority in Hainan, China, into a computational media artwork. Conducted as part of an on-site art residency, this project integrates field research, machine learning, and digital media to reinterpret Li brocade patterns in a contemporary digital context. Using a curated dataset of traditional Li brocade pattern designs, a customized small-scale neural network generates evolving brocade motifs, which are then incorporated into a dynamic projection-based installation. This paper examines the history and contemporary practice of Li brocade craft, documents the computation design process, as well as the public exhibition of Viu, showcasing how computational media art can serve as a medium to invigorate appreciation for the Li brocade cultural heritage, and the potential of computational methods and machine learning in promoting traditional cultural heritage.

This study investigates the use of generative AI with the Rorschach Inkblot Test to support emotional exploration and self-expression. A controlled experiment compared static images with AI-generated dynamic visuals, and expert interviews provided professional insights. Results indicate that dynamic visuals can deepen emotional exploration, enrich narratives, and expand self-expression, though individual differences and content variability remain challenges. This work offers a novel methodology for integrating generative AI into psychological assessment and creative arts while highlighting its potential and ethical considerations.

This paper introduces Cave, an AI-generated experimental short film that reinterprets Plato’s “Allegory of the Cave” and the “Brain in a Vat” thought experiment in the context of AI. Following the story of Ellie, who is trapped in a virtual world controlled by an AI system, the film reflects on the ethical risks of technologies that reshape human perception and blur reality and virtuality. Produced entirely with generative AI tools like Kling AI, Runway, and ElevenLabs, the project demonstrates a full narrative film production process while exploring questions of consciousness, free will, and reality.

Although virtual production (VP) offers cinematic and immersive storytelling by aligning a high-end camera with multiple LED screens through a central server, the creation of high-quality 3D scenery with real-time interactions remains complex and resource-intensive. This paper explores the potential of expanding cinematic virtual production scenes through three innovative AI-driven approaches: (1) AI-generated 360° panoramas from text prompts to produce immersive backgrounds; (2) Direct text/AI-generated image-to-3D environment conversion using mesh generation; (3) An end-to-end AI pipeline for rapid stylized scene construction. We demonstrate each workflow through real-time avatar-interactive shooting scenarios. Our approach bridges technical and artistic domains and aims to show how these AI-driven workflows could accelerate scene creation, enable novel cinematic experiences, and reveal the future potential of visual content generation.

This paper introduces a novel framework for human–AI collaborative storytelling using split-screen narrative techniques. Moving beyond conventional AI applications in visual reproduction, we develop a co-creative workflow that integrates computational capabilities with Chinese aesthetic principles to address challenges in temporal and spatial narrative design. Through a case study of The Legend of the White Snake, we demonstrate how AI enhances the symbolic representation of duality, while human expertise ensures cultural authenticity. Key findings include: (1) AI improves efficiency in generating parallel visual sequences and maintaining stylistic consistency; (2) human intervention is essential for contextualizing cultural symbols and emotional resonance; (3) the hybrid approach enables innovative visual storytelling that both respects tradition and expands creative possibilities. This research contributes to culturally-grounded AI applications in digital heritage and narrative innovation.

We present “The Urban Legend of the Gas Lamp," an innovative AI-enhanced interactive story that transforms urban legends from passively heard tales into immersive investigative experiences. Set in 1990s Hong Kong, our project creates an immersive mystery where players don’t just hear about supernatural events—they witness and experience them firsthand. By incorporating pre-generated character videos within a fully explorable Unreal Engine 5 environment, we demonstrate how AI-generated content serves as emotional anchors that make the impossible feel inevitable. Our technical framework seamlessly integrates 2D generated content into 3D game spaces, where AI-generated videos function as narrative clues, emotional touchstones, and visual guides—including portal-style displays that help players choose their path and create moments where skepticism transforms into belief. Through this experiential design, audiences engage in visceral detective work, discovering that some mysteries are better left unsolved—yet impossible to resist.

Narrative visualization facilitates data presentation and communicates insights, while virtual reality can further enhance immersive and engaging experiences. The combination of these two research interests shows the potential to revolutionize the way data is presented and understood. Within the realm of narrative visualization, empirical evidence has particularly highlighted the importance of camera planning. However, existing works primarily rely on user-intensive manipulation of the camera, with little effort put into automating the process. To fill the gap, this paper proposes CineFolio , a semi-automated camera planning method to reduce manual effort and enhance user experience in immersive narrative visualization. CineFolio combines cinematic theories with graphics criteria, considering both information delivery and aesthetic enjoyment to ensure a comfortable and engaging experience. Specifically, we parametrize the considerations into optimizable camera properties and solve it as a constraint satisfaction problem (CSP) to realize common camera types for narrative visualization, namely overview camera for absorbing the scale, focus camera for detailed views, moving camera for animated transitions, and user-controlled camera allowing users to provide inputs to camera planning. We demonstrate the feasibility of our approach with cases of various data and chart types. To further evaluate our approach, we conducted a within-subject user study, comparing our automated method with manual camera control, and the results confirm both effectiveness of the guided navigation and expressiveness of the cinematic design for narrative visualization.

Drawing its name from the Uyghur expression for’dance on silk,’’DanceYipékda’ epitomizes the elegance and fluidity of cultural expression that this installation seeks to embody. This project unites the realms of AI-generated calligraphy, projection mapping, and 3D printing to weave a narrative as intricate as silk itself—reflecting the complexity and beauty of cross-cultural communication. Leveraging cutting-edge AI technologies, the artwork initiates the creative process by generating 2D calligraphic art, which is subsequently transformed into a 3D format, further accentuated with dynamic projection mapping that breathes life and color into the static forms. As a multimedia art installation,’DanceYipékda’ brings to life the ancient tradition of calligraphy, employing technology as a bridge between historical art forms and contemporary artistic expression. It is a dialogue across time, a dance of light and shadow, sparking a transformative conversation on the convergence of art, technology, and society, encouraging viewers to construct a collective understanding that surpasses linguistic and geographical barriers.

Storytelling is vital to children’s development by nurturing creative thinking, effective communication, and self-expression. Many tools have been created to support children’s creativity. Unfortunately, the existing tools do not adequately integrate visual elements with storytelling, limiting children’s imaginative potential. This study addresses the gap by introducing a proxy visual storytelling tool (PVST) that employs a character-based approach (i.e., proxy character assembling) to enhance children’s creativity and storytelling skills. Through a comparative study using Kurt Vonnegut’s “The Shape of Stories" theory, the PVST was evaluated. The results from a pilot test show that the PVST can increase children’s sense of agency and engagement in the storytelling learning process. Additionally, it can stimulate children’s creative imagination, improve their storytelling abilities, and enable them to construct more fluent and articulate narratives. The findings highlight the importance of incorporating visual storytelling elements in enhancing children’s creativity and storytelling skills, ultimately fostering a more engaging and enriching learning experience.

We present our approach to using AI-generated content (AIGC) and multiple media to develop an immersive, game-based, interactive story experience. The narrative of the story, "Memory Remedy", unfolds through flashbacks, allowing the audience to gradually uncover the story and the complex relationship between the robot protagonist and the older adults. This exploration explores important themes such as the journey of life, the profound influence of memories, and the concept of post-human emotional care. By engaging with this AIGC-based interactive story, audiences are encouraged to reflect on the potential role of robotic companionship in the lives of older adults in the future, and to encourage deeper reflection on the complex relationship between artificial intelligence and humanity.

Star Pilgrim is an experimental short video artwork displayed on a 16:9 screen. It combines Unreal Engine filmmaking with AIGC techniques. The project used Midjourney to generate a customized dataset of stylized images, which was then used as LoRA training data for style transfer applied to the video footage. Additionally, the creative process involved human-AI collaborative generation of original music and poetry. By blending cinematic visuals with AI-powered generative content, this work aims to explore the unique artistic potential of human and machine creativity. Through its experimental approach, Star Pilgrim seeks to push the boundaries of conventional filmmaking, offering a dreamlike and hyper-real interpretation of the concept.

Data videos are becoming increasingly popular in society and academia. Yet little is known about how to create endings that strengthen a lasting impression and persuasion. To fulfill the gap, this work aims to develop guidelines for data video endings by drawing inspiration from cinematic arts. To contextualize cinematic endings in data videos, 111 film endings and 105 data video endings are first analyzed to identify four common styles using the framework of ending punctuation marks. We conducted expert interviews (N=11) and formulated 20 guidelines for creating cinematic endings in data videos. To validate our guidelines, we conducted a user study where 24 participants were invited to design endings with and without our guidelines, which are evaluated by experts and the general public. The participants praise the clarity and usability of the guidelines, and results show that the endings with guidelines are perceived to be more understandable, impressive, and reflective.

Artificial Intelligent Generation Content (AIGC), has been widely disseminated in the fields of technology, academia, and the arts. This project explores the application of various AI tools and the visualization of dream experiences through multimedia. It utilizes AI-generated multimodal materials as perceptible dream content, employs light and mechanical installations to create immersive dream atmospheres, and employs a fictional AI-Mulan narrator to recount her dream story. Through artistic practice, it delves into Mulan's unconscious realm and conducts a psychoanalysis of a historical figure. It represents an interdisciplinary exploration of art and psychoanalysis through AI visualization.

This paper explores the concept of expanded cinema and its relationship to extended reality (XR), focusing on the potential of artificial intelligence (AI) to expand and extend expressive possibilities. Expanded cinema refers to experimental film and multimedia art forms that challenge the conventions of traditional cinema by creating immersive and interactive experiences for audiences. XR, on the other hand, blurs the line between physical and virtual reality, offering immersive storytelling experiences. Both expanded cinema and XR aim to push the boundaries of traditional norms and create immersive experiences through the integration of technology, interactivity, and cross-sensory elements. The paper emphasizes the role of AI in optimizing 3D scene creation for XR and enhancing the overall experience through a case study. It also presents several AI-based techniques, such as generative models and AI-assisted rendering, that facilitate efficient and effective 3D content creation. Additionally, it explores the use of AI plugins in 3D modeling software and the generation of 3D models and textures from 2D images using techniques like GANs and VAEs. The incorporation of AI to extend and expand opens up new possibilities for immersive experiences in the future.

We present an interactive story named Simonstown that demonstrates the love and life of ordinary people in the fictional setting of a fatal pandemic. Technically, the artwork integrates different Artificial Intelligence (AI) technologies in the whole production pipeline, including concept formation, creation, and presentation stages; artistically, this interactive film explores the relationship between human and environment in the contemporary context, especially infused with advanced technologies in daily life. The project serves as a demonstration and case study of AI-facilitated interactive storytelling, including better control with AI and how they integrate with live image projects, as well as using the stand-alone camera for real-time synchronization. Our results highlight the significant contribution of AI in visualizing intricate story branching, translation, and adaptation, presenting AI visualization as a distinct, specialized, and well-suited tool for interactive filmmaking.

Data videos are an increasingly popular storytelling form. The opening of a data video critically influences its success as the opening either attracts the audience to continue watching or bores them to abandon watching. However, little is known about how to create an attractive opening. We draw inspiration from the openings of famous films to facilitate designing data video openings. First, by analyzing over 200 films from several sources, we derived six primary cinematic opening styles adaptable to data videos. Then, we consulted eight experts from the film industry to formulate 28 guidelines. To validate the usability and effectiveness of the guidelines, we asked participants to create data video openings with and without the guidelines, which were then evaluated by experts and the general public. Results showed that the openings designed with the guidelines were perceived to be more attractive, and the guidelines were praised for clarity and inspiration.