37 citations · 77 across the 18 of their papers we have counts for
19 papers
RMMBench: A Comprehensive Benchmark for Robotic Mobile Manipulation
Huapeng Li, Fuxiang Feng, Jinqiu Fan +5
Although the advancement of vision-language models (VLMs) has endowed robots with enhanced environmental understanding and task reasoning, a comprehensive evaluation methodology is…
DRL-TH: Jointly Utilizing Temporal Graph Attention and Hierarchical Fusion for UGV Navigation in Crowded Environments
Ruitong Li, Lin Zhang, Yuenan Zhao +3
Deep reinforcement learning (DRL) methods have demonstrated potential for autonomous navigation and obstacle avoidance of unmanned ground vehicles (UGVs) in crowded environments. M…
Informative Text-Image Alignment for Visual Affordance Learning with Foundation Models
Qian Zhang, Lin Zhang, Xing Fang +4
Visual affordance learning is crucial for robots to understand and interact effectively with the physical world. Recent advances in this field attempt to leverage pre-trained knowl…
StyleLoco: Generative Adversarial Distillation for Natural Humanoid Robot Locomotion
Le Ma, Ziyu Meng, Tengyu Liu +4
Humanoid robots are anticipated to acquire a wide range of locomotion capabilities while ensuring natural movement across varying speeds and terrains. Existing methods encounter a…
Coarse-to-Fine Detection of Multiple Seams for Robotic Welding
Pengkun Wei, Shuo Cheng, Dayou Li +3
Efficiently detecting target weld seams while ensuring sub-millimeter accuracy has always been an important challenge in autonomous welding, which has significant application in in…
Where to Fetch: Extracting Visual Scene Representation from Large Pre-Trained Models for Robotic Goal Navigation
Yu Li, Dayou Li, Chenkun Zhao +3
To complete a complex task where a robot navigates to a goal object and fetches it, the robot needs to have a good understanding of the instructions and the surrounding environment…
MPGNet: Learning Move-Push-Grasping Synergy for Target-Oriented Grasping in Occluded Scenes
Dayou Li, Chenkun Zhao, Shuo Yang +3
This paper focuses on target-oriented grasping in occluded scenes, where the target object is specified by a binary mask and the goal is to grasp the target object with as few robo…
Integrating Controllable Motion Skills from Demonstrations
Honghao Liao, Zhiheng Li, Ziyu Meng +3
The expanding applications of legged robots require their mastery of versatile motion skills. Correspondingly, researchers must address the challenge of integrating multiple divers…
VLMPC: Vision-Language Model Predictive Control for Robotic Manipulation
Wentao Zhao, Jiaming Chen, Ziyu Meng +3
Although Model Predictive Control (MPC) can effectively predict the future states of a system and thus is widely used in robotic manipulation tasks, it does not have the capability…
SoccerNet 2023 Challenges Results
Anthony Cioppa, Silvio Giancola, Vladimir Somers +99
The SoccerNet 2023 challenges were the third annual video understanding challenges organized by the SoccerNet team. For this third edition, the challenges were composed of seven vi…
Point-aware Interaction and CNN-induced Refinement Network for RGB-D Salient Object Detection
Runmin Cong, Hongyu Liu, Chen Zhang +4
By integrating complementary information from RGB image and depth map, the ability of salient object detection (SOD) for complex and challenging scenes can be improved. In recent y…
Network Pruning Spaces
Xuanyu He, Yu-I Yang, Ran Song +5
Network pruning techniques, including weight pruning and filter pruning, reveal that most state-of-the-art neural networks can be accelerated without a significant performance drop…
Circular Accessible Depth: A Robust Traversability Representation for UGV Navigation
Shikuan Xie, Ran Song, Yuenan Zhao +3
In this paper, we present the Circular Accessible Depth (CAD), a robust traversability representation for an unmanned ground vehicle (UGV) to learn traversability in various scenar…
SoccerNet 2022 Challenges Results
Silvio Giancola, Anthony Cioppa, Adrien Deliège +91
The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team. In 2022, the challenges were composed of 6 vision-based tasks:…
Learning Point-Language Hierarchical Alignment for 3D Visual Grounding
Jiaming Chen, Weixin Luo, Ran Song +3
This paper presents a novel hierarchical alignment model (HAM) that learns multi-granularity visual and linguistic representations in an end-to-end manner. We extract key points an…
Provably Uncertainty-Guided Universal Domain Adaptation
Yifan Wang, Lin Zhang, Ran Song +3
Universal domain adaptation (UniDA) aims to transfer the knowledge from a labeled source domain to an unlabeled target domain without any assumptions of the label sets, which requi…
Exploiting Inter-Sample Affinity for Knowability-Aware Universal Domain Adaptation
Yifan Wang, Lin Zhang, Ran Song +3
Universal domain adaptation (UniDA) aims to transfer the knowledge of common classes from the source domain to the target domain without any prior knowledge on the label set, which…
Take More Positives: An Empirical Study of Contrastive Learing in Unsupervised Person Re-Identification
Xuanyu He, Wei Zhang, Ran Song +3
Unsupervised person re-identification (re-ID) aims at closing the performance gap to supervised methods. These methods build reliable relationship between data points while learnin…
Learn by Observation: Imitation Learning for Drone Patrolling from Videos of A Human Navigator
Yue Fan, Shilei Chu, Wei Zhang +2
We present an imitation learning method for autonomous drone patrolling based only on raw videos. Different from previous methods, we propose to let the drone learn patrolling in t…