67 citations · 102 across the 10 of their papers we have counts for
12 papers
Relational Geometry Forcing for World Action Models
Yuan Xu, Yixiang Chen, Qisen Ma +10
World Action Models (WAMs) have shown strong potential for robot manipulation by jointly learning visual dynamics and executable actions. However, their video and action objectives…
What Matters for World Modeling in Vision-Language-Action Models?
Qisen Ma, Yixiang Chen, Yuan Xu +10
Integrating world models into Vision-Language-Action models (VLAs) has emerged as a promising direction, enabling policies to anticipate future dynamics beyond reactive observation…
GuardianBench: A Same-Scene Instruction-Contrastive Benchmark for Latent Contextual Risk in Embodied AI
Zhesheng Zhang, Jiahao Lu, Wei Liu +8
In embodied AI, safety risk can be latent: a benign instruction and a safe scene become hazardous only when composed. Prior work has advanced embodied safety by varying visual cont…
UESF-Bench: Benchmarking and Probing for Unified Embodied Seeking and Following
Kun Yu, Jianhua Yang, Yixiang Chen +7
Language-guided human following is an important capability for embodied agents, but existing benchmarks typically assume that the target person is visible at the start of an episod…
FlowWAM: Optical Flow as a Unified Action Representation for World Action Models
Yixiang Chen, Peiyan Li, Yuan Xu +13
World Action Models (WAMs) are able to leverage pretrained video generators for both world modeling and action prediction. However, directly leveraging such video generators for co…
YOWOv2: A Stronger yet Efficient Multi-level Detection Framework for Real-time Spatio-temporal Action Detection
Jianhua Yang, Kun Dai
Designing a real-time framework for the spatio-temporal action detection task is still a challenge. In this paper, we propose a novel real-time action detection framework, YOWOv2.…
YOWO-Plus: An Incremental Improvement
Jianhua Yang
In this technical report, we would like to introduce our updates to YOWO, a real-time method for spatio-temporal action detection. We make a bunch of little design changes to make…
JPEG Steganography with Embedding Cost Learning and Side-Information Estimation
Jianhua Yang, Yi Liao, Fei Shang +2
A great challenge to steganography has arisen with the wide application of steganalysis methods based on convolutional neural networks (CNNs). To this end, embedding cost learning…
CMF: Cascaded Multi-model Fusion for Referring Image Segmentation
Jianhua Yang, Yan Huang, Zhanyu Ma +1
In this work, we address the task of referring image segmentation (RIS), which aims at predicting a segmentation mask for the object described by a natural language expression. Mos…
Actor and Action Modular Network for Text-based Video Segmentation
Jianhua Yang, Yan Huang, Kai Niu +3
Text-based video segmentation aims to segment an actor in video sequences by specifying the actor and its performing action with a textual query. Previous methods fail to explicitl…
Spatial Image Steganography Based on Generative Adversarial Network
Jianhua Yang, Kai Liu, Xiangui Kang +2
With the recent development of deep learning on steganalysis, embedding secret information into digital images faces great challenges. In this paper, a secure steganography algorit…
JPEG Steganalysis Based on DenseNet
Jianhua Yang, Yun-Qing Shi, Edward K. Wong +1
Different from the conventional deep learning work based on an images content in computer vision, deep steganalysis is an art to detect the secret information embedded in an image…