20 citations · 21 across the 5 of their papers we have counts for
5 papers
StableVLA: Towards Robust Vision-Language-Action Models without Extra Data
Yiyang Fu, Chubin Zhang, Shukai Gong +7
It is infeasible to encompass all possible disturbances within the training dataset. This raises a critical question regarding the robustness of Vision-Language-Action (VLA) models…
Bernini: Latent Semantic Planning for Video Diffusion
Bernini Team, Chenchen Liu, Junyi Chen +9
Multimodal large language models (MLLMs) and diffusion models have each reached remarkable maturity: MLLMs excel at reasoning over heterogeneous multimodal inputs with strong seman…
Collaborative Tracking Learning for Frame-Rate-Insensitive Multi-Object Tracking
Yiheng Liu, Junta Wu, Yi Fu
Multi-object tracking (MOT) at low frame rates can reduce computational, storage and power overhead to better meet the constraints of edge devices. Many existing MOT methods suffer…
Coherent Loss: A Generic Framework for Stable Video Segmentation
Mingyang Qian, Yi Fu, Xiao Tan +5
Video segmentation approaches are of great importance for numerous vision tasks especially in video manipulation for entertainment. Due to the challenges associated with acquiring…
Exploiting Spatial-Temporal Modelling and Multi-Modal Fusion for Human Action Recognition
Dongliang He, Fu Li, Qijie Zhao +3
In this report, our approach to tackling the task of ActivityNet 2018 Kinetics-600 challenge is described in detail. Though spatial-temporal modelling methods, which adopt either s…