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20222026
most citedCLIP-Count: Towards Text-Guided Zero-Shot Object Counting

75 citations · 96 across the 9 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

On Semiotic-Grounded Interpretive Evaluation of Generative Art

Ruixiang Jiang, Changwen Chen

Interpretation is essential to deciphering the language of art: audiences communicate with artists by recovering meaning from visual artifacts. However, current Generative Art (Gen…

cs.CV2025★ 5 cited

Multimodal LLMs Can Reason about Aesthetics in Zero-Shot

Ruixiang Jiang, Changwen Chen

The rapid technical progress of generative art (GenArt) has democratized the creation of visually appealing imagery. However, achieving genuine artistic impact - the kind that reso…

cs.CV2024★ 4 cited

DiffArtist: Towards Structure and Appearance Controllable Image Stylization

Ruixiang Jiang, Changwen Chen

Artistic styles are defined by both their structural and appearance elements. Existing neural stylization techniques primarily focus on transferring appearance-level features such…

cs.CV2023★ 75 cited

CLIP-Count: Towards Text-Guided Zero-Shot Object Counting

Ruixiang Jiang, Lingbo Liu, Changwen Chen

Recent advances in visual-language models have shown remarkable zero-shot text-image matching ability that is transferable to downstream tasks such as object detection and segmenta…

cs.CV2023★ 3 cited

AvatarCraft: Transforming Text into Neural Human Avatars with Parameterized Shape and Pose Control

Ruixiang Jiang, Can Wang, Jingbo Zhang +4

Neural implicit fields are powerful for representing 3D scenes and generating high-quality novel views, but it remains challenging to use such implicit representations for creating…

cs.CV2022★ 7 cited

NeRF-Art: Text-Driven Neural Radiance Fields Stylization

Can Wang, Ruixiang Jiang, Menglei Chai +3

As a powerful representation of 3D scenes, the neural radiance field (NeRF) enables high-quality novel view synthesis from multi-view images. Stylizing NeRF, however, remains chall…