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Jixuan Ying

5 accepted papers

2026

Bridging Cognitive Gap: Hierarchical Description Learning for Artistic Image Aesthetics Assessment

AAAI 2026technical

The aesthetic quality assessment task is crucial for developing a human-aligned quantitative evaluation system for AIGC. However, its inherently complex nature—spanning visual perception, cognition, and emotion—poses fundamental challenges. Although aesthetic descriptions offer a viable representati

Cited by 2SourcePDFScholar
2026

Group Editing: Edit Multiple Images in One Go

CVPR 2026

In this paper, we tackle the problem of performing consistent and unified modifications across a set of related images. This task is particularly challenging because these images may vary significantly in pose, viewpoint, and spatial layout. Achieving coherent edits requires establishing reliable co

Cited by 0SourcecodeScholar
2025

Follow-Your-Click: Open-domain Regional Image Animation via Motion Prompts

AAAI 2025technical

Despite recent advances in image-to-video generation, better controllability and local animation are less explored. Most existing image-to-video methods are not locally aware and tend to move the entire scene. However, human artists may need to control the movement of different objects or regions. A…

Cited by 52SourcePDFScholar
2025

Harmonious Music-driven Group Choreography with Trajectory-Controllable Diffusion

AAAI 2025technical

Creating group choreography from music is crucial in cultural entertainment and virtual reality, with a focus on generating harmonious movements. Despite growing interest, recent approaches often struggle with two major challenges: multi-dancer collisions and single-dancer foot sliding. To address…

Cited by 0SourcePDFScholar
2025

Linear Differential Vision Transformer: Learning Visual Contrasts via Pairwise Differentials

NeurIPS 2025poster

Vision Transformers (ViTs) have become a universal backbone for both image recognition and image generation. Yet their Multi–Head Self–Attention (MHSA) layer still performs a quadratic query–key interaction for \emph{every} token pair, spending the bulk of computation on visually weak or redundant…

Cited by 0SourcecodeScholar