activity
20182025
most citedAttention to Head Locations for Crowd Counting

16 citations · 16 across the 8 of their papers we have counts for

collaborators

8 papers

cs.RO2025

ForeRobo: Unlocking Infinite Simulation Data for 3D Goal-driven Robotic Manipulation

Dexin wang, Faliang Chang, Chunsheng Liu

Efficiently leveraging simulation to acquire advanced manipulation skills is both challenging and highly significant. We introduce \textit{ForeRobo}, a generative robotic agent tha…

cs.RO2024

Goal State Generation for Robotic Manipulation Based on Linguistically Guided Hybrid Gaussian Diffusion

Yichen Xu, Faliang Chang, Chunsheng Liu +1

In robotic manipulation tasks, achieving a designated target state for the manipulated object is often essential to facilitate motion planning for robotic arms. Specifically, in ta…

cs.RO2024

Hierarchical Diffusion Policy: manipulation trajectory generation via contact guidance

Dexin Wang, Chunsheng Liu, Faliang Chang +1

Decision-making in robotics using denoising diffusion processes has increasingly become a hot research topic, but end-to-end policies perform poorly in tasks with rich contact and…

cs.CV2024

EraW-Net: Enhance-Refine-Align W-Net for Scene-Associated Driver Attention Estimation

Jun Zhou, Chunsheng Liu, Faliang Chang +4

Associating driver attention with driving scene across two fields of views (FOVs) is a hard cross-domain perception problem, which requires comprehensive consideration of cross-vie…

cs.RO2023

Multi-Stage Reinforcement Learning for Non-Prehensile Manipulation

Dexin Wang, Faliang Chang, Chunsheng Liu

Manipulating objects without grasping them enables more complex tasks, known as non-prehensile manipulation. Most previous methods only learn one manipulation skill, such as reach…

cs.RO2022

On-Policy Pixel-Level Grasping Across the Gap Between Simulation and Reality

Dexin Wang, Faliang Chang, Chunsheng Liu +3

Grasp detection in cluttered scenes is a very challenging task for robots. Generating synthetic grasping data is a popular way to train and test grasp methods, as is Dex-net and Gr…

cs.CV2020

Guidance Module Network for Video Captioning

Xiao Zhang, Chunsheng Liu, Faliang Chang

Video captioning has been a challenging and significant task that describes the content of a video clip in a single sentence. The model of video captioning is usually an encoder-de…

cs.CV2018★ 16 cited

Attention to Head Locations for Crowd Counting

Youmei Zhang, Chunluan Zhou, Faliang Chang +1

Occlusions, complex backgrounds, scale variations and non-uniform distributions present great challenges for crowd counting in practical applications. In this paper, we propose a n…