activity
20232026
most citedCNS-Edit: 3D Shape Editing via Coupled Neural Shape Optimization

3 citations · 4 across the 16 of their papers we have counts for

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11 papers · 1 filter

cs.CV2026

FACT: A Forensic Agent with Compiled Tool-Use Trajectories for AI-Generated Image Detection

Jiaoyang Chen, Bin Hu, Jingyu Hu +3

AI-generated image detection is increasingly open-world: new image generators produce highly realistic images that make visual artifacts harder to identify. Existing detectors usua…

cs.CV2026

FuncRoom-Agent: Sequential Feed-Forward 3D Functional Indoor Scene Generation

Hao Feng, Zhi Zuo, MingJian Liang +6

We introduce Function-Room Generation, a new indoor 3D scene generation setting that creates rooms supporting explicit functional goals rather than merely visually plausible layout…

cs.CV2026

CNS-Edit++: Category-Agnostic 3D Editing with Coupled Neural Shape Representation

Jingyu Hu, Weilong Yan, Zhengzhe Liu +4

This paper presents a latent-space 3D shape editing framework built upon a coupled neural shape (CNS) representation and a neural feature volume optimization. This work extends CNS…

cs.CV2026

SkelGen4D: Weakly-Supervised Skeleton-Based 4D Generation for Text-Driven Mesh Animation

Hao Feng, Zhi Zuo, Jia-Hui Pan +6

We study 4D generation to synthesize temporally coherent sequences of 3D geometry for animation and content creation. In contrast to existing SDS-based optimization methods and vid…

cs.CV2026

PhyMix: Towards Physically Consistent Single-Image 3D Indoor Scene Generation with Implicit--Explicit Optimization

Dongli Wu, Jingyu Hu, Ka-Hei Hui +4

Existing methods for single-image 3D indoor scene generation often produce visually plausible results that violate real-world physical constraints, limiting their reliability in ro…

cs.CV2026

LaS-Comp: Zero-shot 3D Completion with Latent-Spatial Consistency

Weilong Yan, Haipeng Li, Hao Xu +4

This paper introduces LaS-Comp, a zero-shot and category-agnostic approach that leverages the rich geometric priors of 3D foundation models to enable 3D shape completion across div…

cs.CV2026

coDrawAgents: A Multi-Agent Dialogue Framework for Compositional Image Generation

Chunhan Li, Qifeng Wu, Jia-Hui Pan +7

Text-to-image generation has advanced rapidly, but existing models still struggle with faithfully composing multiple objects and preserving their attributes in complex scenes. We p…

cs.CV2026

Action-Geometry Prediction with 3D Geometric Prior for Bimanual Manipulation

Chongyang Xu, Haipeng Li, Shen Cheng +4

Bimanual manipulation requires policies that can reason about 3D geometry, anticipate how it evolves under action, and generate smooth, coordinated motions. However, existing metho…

cs.CV2026

Imagine a City: CityGenAgent for Procedural 3D City Generation

Zishan Liu, Zecong Tang, RuoCheng Wu +6

The automated generation of interactive 3D cities is a critical challenge with broad applications in autonomous driving, virtual reality, and embodied intelligence. While recent ad…

cs.CV2026

PEGAsus: 3D Personalization of Geometry and Appearance

Jingyu Hu, Bin Hu, Ka-Hei Hui +4

We present PEGAsus, a new framework capable of generating Personalized 3D shapes by learning shape concepts at both Geometry and Appearance levels. First, we formulate 3D shape per…

cs.CY2026

Failing on Bias Mitigation: A Case Study on the Challenges of Fairness in Government Data

Hongbo Bo, Jingyu Hu, Debbie Watson +1

The potential for bias and unfairness in AI-supporting government services raises ethical and legal concerns. Using crime rate prediction with the Bristol City Council data as a ca…