20 papers · 1 filter
AnyMo: Scaling Any-Modality Conditional Motion Generation with Masked Modeling
Yiheng Li, Zhuo Li, Ruibing Hou +4
Conditional human motion generation remains a fundamental challenge in computer vision and robotics. Despite significant progress, current methods are often constrained by fixed mo…
Component-Based Out-of-Distribution Detection
Wenrui Liu, Hong Chang, Ruibing Hou +2
Out-of-Distribution (OOD) detection requires sensitivity to subtle shifts without overreacting to natural In-Distribution (ID) diversity. However, from the viewpoint of detection g…
EgoMotion: Hierarchical Reasoning and Diffusion for Egocentric Vision-Language Motion Generation
Ruibing Hou, Mingyue Zhou, Yuwei Gui +5
Faithfully modeling human behavior in dynamic environments is a foundational challenge for embodied intelligence. While conditional motion synthesis has achieved significant advanc…
DreamActor-M2: Universal Character Image Animation via Spatiotemporal In-Context Learning
Mingshuang Luo, Shuang Liang, Zhengkun Rong +7
Character image animation aims to synthesize high-fidelity videos by transferring motion from a driving sequence to a static reference image. Despite recent advancements, existing…
CLIP-Guided Adaptable Self-Supervised Learning for Human-Centric Visual Tasks
Mingshuang Luo, Ruibing Hou, Bo Chao +4
Human-centric visual analysis plays a pivotal role in diverse applications, including surveillance, healthcare, and human-computer interaction. With the emergence of large-scale un…
Revisiting Logit Distributions for Reliable Out-of-Distribution Detection
Jiachen Liang, Ruibing Hou, Minyang Hu +3
Out-of-distribution (OOD) detection is critical for ensuring the reliability of deep learning models in open-world applications. While post-hoc methods are favored for their effici…