This study examines the development, status, and future trends of China’s urban night tourism industry. Through a comprehensive analysis of historical progression, market scale, and technological transformation, this research provides insights into the evolving landscape of urban night tourism in China. The industry has undergone significant growth, with the night-time economy reaching 4.8 trillion yuan in 2023, becoming a crucial component of urban economic development. The study identifies two main categories of urban night tourism products: cultural night tourism and sightseeing night tourism, each offering unique experiences that showcase local culture and urban landscapes. Technological advancements, particularly in intelligent lighting, virtual and augmented reality, and IoT, have substantially enhanced the quality and appeal of night tourism experiences. The research also highlights the development of night tourism in key cities such as Chongqing, Shanghai, and Changsha, supported by favourable policies and diverse product offerings. Looking ahead, the digital transformation of the industry presents both opportunities and challenges, with a focus on balancing technological innovation with authentic experiences. The study concludes by proposing innovation paths for the industry, emphasising product diversification, service quality improvement, and stakeholder collaboration to ensure sustainable growth and competitiveness in the tourism market.

Narrative understanding requires going beyond local content to capture the overall development and organization of a story. Emotion dynamics and narrative organization reflect how a story is experienced and constructed, respectively, and constitute two interrelated dimensions of multi-image narrative understanding. However, existing work typically examines them in separate task and evaluation settings, leaving their relationship within the same narrative underexplored. In this work, we focus on multi-image narrative understanding, using picture books as a representative setting, and formulate two interrelated tasks: reader-side affective experience and author-side narrative organization. We introduce Emo-FOLIO, a benchmark comprising 234 picture books drawn from Chinese- and English-language sources and 4,173 image--text pages, with annotations and evaluation at the page, transition, and stage levels. We further propose Multilevel Organization of Story-Aware Information for Cross-level Reasoning (MOSAIC), a structured inference framework that constructs a reusable narrative scaffold from multimodal evidence, jointly infers narrative stages and their communicative intents, and conditions local emotion estimation on the predicted structure while preserving cross-window continuity. Experiments with eight multimodal backbones reveal marked capability divergence: strong page-level recognition does not reliably translate into cross-page trend estimation or stage-level understanding. Across four representative backbones, MOSAIC improves over direct whole-book inference by averages of 2.6, 7.2, and 6.8 percentage points in page-level multilabel emotion recognition, cross-page emotion trend estimation, and joint stage-and-intent recovery, respectively. These results show that explicit organization of narrative evidence and structure-guided inference provide an effective way to connect local and global understanding in sequential multimodal narratives.

Visual affect analysis typically predicts a static emotion label for an image. However, emotional responses to artworks often evolve as viewers move from rapid visual impression to detailed observation and contextual interpretation. To model this evolution, we formulate artistic image affective trajectory prediction, which predicts a three-stage sequence of emotion labels for the same artwork as observational and contextual evidence progressively increases. We construct ArtArc, an artistic image affective trajectory benchmark with 3,210 artworks. Each sample includes a title, a description, and human-annotated affective trajectories, covering over 13K stage-level emotion-label entries. ArtArc allows both single- and dual-label annotations to reflect the ambiguity of artistic affect. We further propose Artistic-image Affective Trajectory Inference with Dynamic Evidence (ArtTIDE), a training-free structured reasoning framework that guides multimodal large language models to update affective judgments through global visual evidence, visual-semantic evidence, and textual-contextual evidence. Experiments on five representative multimodal models show that the proposed benchmark remains challenging, especially for fine-grained emotion recognition. ArtTIDE consistently improves stage-level prediction, trajectory matching, and context-aware updating over the base setting, increasing the three-stage soft matching rate and contextual supplementation gain rate by 9.2 and 9.0 percentage points, respectively, while reducing the context regression rate by 5.8 percentage points. Ablation experiments and case studies further indicate that the structured integration of visual, semantic, and textual evidence is important for modeling affective trajectories in artistic images.

Driven by advances in artificial intelligence, immersive technologies, and related digital innovations, public cultural spaces are undergoing significant mediatization. Although architectural research has addressed this transformation through media architecture, responsive architecture, digital architecture, and intelligent architecture, it has largely focused on urban-scale interfaces or treated media as an external addition to space. To address this gap, this study examines mediated space at the interior scale of public cultural spaces and proposes a holistic analytical framework that understands media as an intrinsic condition of spatial operation. Through literature review, case analysis, and theoretical modeling, mediated space is classified into four types: physical, digital, interactive, and intelligent. The concept of the Spatial Organism is then introduced and structured into three interrelated entities: the media functional entity, the information exchange entity, and the symbolic representation entity. Building on this framework, the study develops a space–user perceptual interaction model and identifies four interaction stages and three interaction modes. The study argues that media intervention is reshaping spatial organization, meaning production, and evaluation, with interactivity, adaptability, and operational capacity as key evaluative dimensions. It thus offers a mechanism-oriented framework for understanding the mediatization of contemporary public cultural spaces.

Existing virtual human generation methods often inadequately preserve individual attributes, lack coherent visual-semantic mapping, and insufficiently integrate regional cultural features. To address these limitations, this study proposes a controllable generation method combining human attribute recognition, visual-semantic mapping, and conditional image generation, using visual features of Yangtze River aquatic organisms as the application context. The system recognizes age group, gender, clothing category, and clothing colour from an input human image and encodes these attributes into a structured representation. A visual-semantic mapping mechanism then links human attributes with fish-specific colour, texture, and morphological features, converting them into structured generation descriptions. These descriptions guide a generative model to produce mermaid-like virtual characters that retain key human attributes while incorporating distinctive fish-inspired visual elements. Experimental results indicate stable performance in attribute consistency, structural integrity, visual-style controllability, and applicability to cultural tourism scenarios. The proposed method establishes an interpretable and extensible pipeline from attribute recognition to cross-domain semantic translation and conditional generation, offering a practical approach to personalized virtual character creation and a methodological reference for the digital presentation of regional ecological and cultural resources.

The emergence and development of light art is established on the maturity of lighting technology and also combined with innovative technology and charm of art, which has been widely applied in the fields of night scene construction, exhibition and festival activities. As the element that is easiest to be captured and felt by vision, light is an essential part of the construction of creative city and gradually becomes a new design outlet in the construction of creative city. On the basis of this, taking China “Dreamy Wuhan” lighting show as an example, the paper analyses the path of light art in the construction of creative city, and also studies the integration of light creation and visual perception. It is expected to enrich the practical research of light art creation in the construction of creative city.