1 citations · 1 across the 3 of their papers we have counts for
6 papers
OmniPrism: Learning Disentangled Visual Concept for Image Generation
Yangyang Li, Daqing Liu, Wu Liu +4
Creative visual concept generation often draws inspiration from specific concepts in a reference image to produce relevant outcomes. However, existing methods are typically constra…
A Paradigm Shift: Fully End-to-End Training for Temporal Sentence Grounding in Videos
Allen He, Qi Liu, Kun Liu +2
Temporal sentence grounding in videos (TSGV) aims to localize a temporal segment that semantically corresponds to a sentence query from an untrimmed video. Most current methods ado…
Motion Capture from Inertial and Vision Sensors
Xiaodong Chen, Wu Liu, Qian Bao +4
Human motion capture is the foundation for many computer vision and graphics tasks. While industrial motion capture systems with complex camera arrays or expensive wearable sensors…
HOIGen-1M: A Large-scale Dataset for Human-Object Interaction Video Generation
Kun Liu, Qi Liu, Xinchen Liu +5
Text-to-video (T2V) generation has made tremendous progress in generating complicated scenes based on texts. However, human-object interaction (HOI) often cannot be precisely gener…
It Takes Two: Accurate Gait Recognition in the Wild via Cross-granularity Alignment
Jinkai Zheng, Xinchen Liu, Boyue Zhang +4
Existing studies for gait recognition primarily utilized sequences of either binary silhouette or human parsing to encode the shapes and dynamics of persons during walking. Silhoue…
SigFormer: Sparse Signal-Guided Transformer for Multi-Modal Human Action Segmentation
Qi Liu, Xinchen Liu, Kun Liu +2
Multi-modal human action segmentation is a critical and challenging task with a wide range of applications. Nowadays, the majority of approaches concentrate on the fusion of dense…