244 citations · 439 across the 46 of their papers we have counts for
12 papers · 2 filters
Guided Path Sampling: Steering Diffusion Models Back on Track with Principled Path Guidance
Haosen Li, Wenshuo Chen, Shaofeng Liang +3
Iterative refinement methods based on a denoising-inversion cycle are powerful tools for enhancing the quality and control of diffusion models. However, their effectiveness is crit…
POLARIS: Projection-Orthogonal Least Squares for Robust and Adaptive Inversion in Diffusion Models
Wenshuo Chen, Haosen Li, Shaofeng Liang +6
The Inversion-Denoising Paradigm, which is based on diffusion models, excels in diverse image editing and restoration tasks. We revisit its mechanism and reveal a critical, overloo…
Learning Time in Static Classifiers
Xi Ding, Lei Wang, Piotr Koniusz +1
Real-world visual data rarely presents as isolated, static instances. Instead, it often evolves gradually over time through variations in pose, lighting, object state, or scene con…
LUMA: Low-Dimension Unified Motion Alignment with Dual-Path Anchoring for Text-to-Motion Diffusion Model
Haozhe Jia, Wenshuo Chen, Yuqi Lin +8
While current diffusion-based models, typically built on U-Net architectures, have shown promising results on the text-to-motion generation task, they still suffer from semantic mi…
Video Understanding by Design: How Datasets Shape Video Models
Lei Wang, Syuan-Hao Li, Piotr Koniusz +1
Research in video understanding has advanced rapidly, driven by increasingly diverse datasets and more powerful model architectures. While existing surveys typically organize progr…
Puzzles: Unbounded Video-Depth Augmentation for Scalable End-to-End 3D Reconstruction
Jiahao Ma, Lei Wang, Miaomiao liu +2
Multi-view 3D reconstruction remains a core challenge in computer vision. Recent methods, such as DUST3R and its successors, directly regress pointmaps from image pairs without rel…
Feature Hallucination for Self-supervised Action Recognition
Lei Wang, Piotr Koniusz
Understanding human actions in videos requires more than raw pixel analysis; it relies on high-level semantic reasoning and effective integration of multimodal features. We propose…
ANT: Adaptive Neural Temporal-Aware Text-to-Motion Model
Wenshuo Chen, Kuimou Yu, Haozhe Jia +8
While diffusion models advance text-to-motion generation, their static semantic conditioning ignores temporal-frequency demands: early denoising requires structural semantics for m…
SRLoRA: Subspace Recomposition in Low-Rank Adaptation via Importance-Based Fusion and Reinitialization
Haodong Yang, Lei Wang, Md Zakir Hossain
Low-Rank Adaptation (LoRA) is a widely adopted parameter-efficient fine-tuning (PEFT) method that injects two trainable low-rank matrices (A and B) into frozen pretrained models. W…
Evolving Skeletons: Motion Dynamics in Action Recognition
Jushang Qiu, Lei Wang
Skeleton-based action recognition has gained significant attention for its ability to efficiently represent spatiotemporal information in a lightweight format. Most existing approa…
Physics-Informed Representation Alignment for Sparse Radio-Map Reconstruction
Haozhe Jia, Wenshuo Chen, Zhihui Huang +7
Radio map reconstruction is essential for enabling advanced applications, yet challenges such as complex signal propagation and sparse observational data hinder accurate reconstruc…
Free-T2M: Robust Text-to-Motion Generation for Humanoid Robots via Frequency-Domain
Wenshuo Chen, Haozhe Jia, Songning Lai +5
Enabling humanoid robots to synthesize complex, physically coherent motions from natural language commands is a cornerstone of autonomous robotics and human-robot interaction. Whil…