1 citations · 1 across the 13 of their papers we have counts for
15 papers
Learning to Beat: Phenotype-Guided Latent Flow with Regional Motion Priors for Biventricular Motion Synthesis
Xuan Yang, Xiaohan Yuan, Hao Li +4
Full-cycle biventricular geometry is essential for characterizing cardiac function. However, dense and temporally consistent 3D+t biventricular meshes are not routinely available,…
Stable Curves, Unstable Items: Item-Level Scaling Heterogeneity in Video LLMs
Wenzhang Sun, Chunfeng Wang, Xiangchen Yin +3
Aggregate scaling curves suggest that Video LLMs improve smoothly or saturate as visual budgets grow. We show that this view can conceal large, opposing changes at the item level.…
Echo4DIR: 4D Implicit Heart Reconstruction from 2D Echocardiography Videos
Yanan Liu, Qinya Li, Hao Zhang +5
Reconstructing 4D (3D+t) cardiac geometry from sparse 2D echocardiography is highly desirable yet fundamentally challenged by geometric ambiguity and temporal discontinuity. To tac…
RePCM: Region-Specific and Phenotype-Adaptive Bi-Ventricular Cardiac Motion Synthesis
Xuan Yang, Xiaohan Yuan, Hao Li +3
Cardiac motion over a cardiac cycle is crucial for quantifying regional function and is strongly affected by cardiovascular diseases. Since temporally dense mesh sequences are diff…
Preserve, Reveal, Expand: Towards Faithful 4D Video Editing with Region-Aware Conditioning and Benchmarking
Zhangchi Hu, Wenzhang Sun, Xiangchen Yin +5
While 4D-driven video diffusion models can generate visually plausible videos, faithful 4D editing poses a stricter requirement: source-observed content should be preserved, while…
Lance: Unified Multimodal Modeling by Multi-Task Synergy
Fengyi Fu, Mengqi Huang, Shaojin Wu +10
We present Lance, a lightweight native unified model supporting multimodal understanding, generation, and editing for both images and videos. Rather than relying on model capacity…
MetricAnything: Scaling Metric Depth Pretraining with Noisy Heterogeneous Sources
Baorui Ma, Jiahui Yang, Donglin Di +5
Scaling has powered recent advances in vision foundation models, yet extending this paradigm to metric depth estimation remains challenging due to heterogeneous sensor noise, camer…
EverybodyDance: Bipartite Graph-Based Identity Correspondence for Multi-Character Animation
Haotian Ling, Zequn Chen, Qiuying Chen +6
Consistent pose-driven character animation has achieved remarkable progress in single-character scenarios. However, extending these advances to multi-character settings is non-triv…
PhysGM: Large Physical Gaussian Model for Feed-Forward 4D Synthesis
Chunji Lv, Zequn Chen, Donglin Di +5
Despite advances in physics-based 3D motion synthesis, current methods face key limitations: reliance on pre-reconstructed 3D Gaussian Splatting (3DGS) built from dense multi-view…
QR-LoRA: Efficient and Disentangled Fine-tuning via QR Decomposition for Customized Generation
Jiahui Yang, Yongjia Ma, Donglin Di +6
Existing text-to-image models often rely on parameter fine-tuning techniques such as Low-Rank Adaptation (LoRA) to customize visual attributes. However, when combining multiple LoR…
ChronoTailor: Harnessing Attention Guidance for Fine-Grained Video Virtual Try-On
Jinjuan Wang, Wenzhang Sun, Ming Li +7
Video virtual try-on aims to seamlessly replace the clothing of a person in a source video with a target garment. Despite significant progress in this field, existing approaches st…
MotionStrata: Hierarchical Motion Latents for Compact Video Autoencoding
Wenzhang Sun, Huaize Liu, Chunfeng Wang +3
First-frame-conditioned video autoencoders represent a clip with persistent content and a compact motion code. Although this removes much of the appearance redundancy, the remainin…
UniAvatar: Taming Lifelike Audio-Driven Talking Head Generation with Comprehensive Motion and Lighting Control
Wenzhang Sun, Xiang Li, Donglin Di +5
Recently, animating portrait images using audio input is a popular task. Creating lifelike talking head videos requires flexible and natural movements, including facial and head dy…
DH-FaceVid-1K: A Large-Scale High-Quality Dataset for Face Video Generation
Donglin Di, He Feng, Wenzhang Sun +6
Human-centric generative models are becoming increasingly popular, giving rise to various innovative tools and applications, such as talking face videos conditioned on text or audi…
GRPose: Learning Graph Relations for Human Image Generation with Pose Priors
Xiangchen Yin, Donglin Di, Lei Fan +6
Recent methods using diffusion models have made significant progress in human image generation with various control signals such as pose priors. However, existing efforts are still…