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cs.CV2026

Unravel: Recovering an Interactive 3D Scene from a Single Image

Hui Shan, Keyang Luo, Binjia Zhou +10

We present Unravel, a training-free framework that turns a single image into an interactive 3D scene, where every object is an independent and movable asset. Existing generators ei…

cs.CV2026

GIFT: Geometry-Invariant Fine-Tuning for Non-Lambertian Monocular Depth Estimation

Xianghui Fan, Zhaoyu Chen, Bingqian Wu +6

Monocular depth foundation models, benefiting from large-scale synthetic training data, have demonstrated strong generalization. However, they often hallucinate depth on non-Lamber…

cs.CV2026

fMRI2Face: A Full-HD fMRI-Video Dataset and Geometry-Guided Neural Decoding Framework for Dynamic Human Face Reconstruction

Jingyang Huo, Xiangru Huang, Chentao Shen +6

Reconstructing dynamic human faces from brain activity provides a powerful way to study how the mind perceives identity, expression, and facial motion. However, progress in fMRI-ba…

cs.CV2026

AudioFace: Language-Assisted Speech-Driven Facial Animation with Multimodal Language Models

Kai Zheng, Zejian Kang, Rui Mao +4

Speech-driven facial animation requires accurate correspondence between acoustic signals and facial motion, especially for articulation-related mouth movements. However, directly m…

cs.CV2026

SuperFace: Preference-Aligned Facial Expression Estimation Beyond Pseudo Supervision

Zejian Kang, Xuanyang Xu, Wentao Yang +6

Accurate facial estimation is crucial for realistic digital human animation, and ARKit blendshape coefficients offer an interpretable representation by mapping facial motions to se…

cs.CV2026

Exploring the Role of Synthetic Data Augmentation in Controllable Human-Centric Video Generation

Yuanchen Fei, Yude Zou, Zejian Kang +3

Controllable human video generation aims to produce realistic videos of humans with explicitly guided motions and appearances,serving as a foundation for digital humans, animation,…

cs.CV2026

SemanticFace: Semantic Facial Action Estimation via Semantic Distillation in Interpretable Space

Zejian Kang, Kai Zheng, Yuanchen Fei +3

Facial action estimation from a single image is often formulated as predicting or fitting parameters in compact expression spaces, which lack explicit semantic interpretability. Ho…

cs.CV2025

Auto3R: Automated 3D Reconstruction and Scanning via Data-driven Uncertainty Quantification

Chentao Shen, Sizhe Zheng, Bingqian Wu +5

Traditional high-quality 3D scanning and reconstruction typically relies on human labor to plan the scanning procedure. With the rapid development of embodied systems such as drone…

cs.CV2025

KeyframeFace: Language-Driven Facial Animation via Semantic Keyframes

Jingchao Wu, Zejian Kang, Haibo Liu +2

Facial animation is a core component for creating digital characters in Computer Graphics (CG) industry. A typical production workflow relies on sparse, semantically meaningful key…