Search Results for author:
Found 15 papers, 8 papers with code
A Survey of Reinforcement Learning-Based Motion Planning for Autonomous Driving: Lessons Learned from a Driving Task Perspective
Reinforcement learning (RL), with its ability to explore and optimize policies in complex, dynamic decision-making tasks, has emerged as a promising approach to addressing motion planning (MoP) challenges in autonomous driving (AD).
PUGS: Zero-shot Physical Understanding with Gaussian Splatting
We propose a new method that reconstructs 3D objects using the Gaussian splatting representation and predicts various physical properties in a zero-shot manner.
Depth Restoration of Hand-Held Transparent Objects for Human-to-Robot Handover
Transparent objects are common in daily life, while their optical properties pose challenges for RGB-D cameras to capture accurate depth information.
Utilizing Large Language Models for Named Entity Recognition in Traditional Chinese Medicine against COVID-19 Literature: Comparative Study
Objective: To explore and compare the performance of ChatGPT and other state-of-the-art LLMs on domain-specific NER tasks covering different entity types and domains in TCM against COVID-19 literature.
Growing from Exploration: A self-exploring framework for robots based on foundation models
In this work, we propose a framework named GExp, which enables robots to explore and learn autonomously without human intervention.
Creating Knowledge Graphs for Geographic Data on the Web
Geographic data plays an essential role in various Web, Semantic Web and machine learning applications.
Learning Quality-aware Dynamic Memory for Video Object Segmentation
However, they mainly focus on better matching between the current frame and the memory frames without explicitly paying attention to the quality of the memory.
Ranked #11 on
Semi-Supervised Video Object Segmentation
on DAVIS 2016
(using extra training data)
Still Haven't Found What You're Looking For -- Detecting the Intent of Web Search Missions from User Interaction Features
Web search is among the most frequent online activities.
SaL-Lightning Dataset: Search and Eye Gaze Behavior, Resource Interactions and Knowledge Gain during Web Search
The emerging research field Search as Learning investigates how the Web facilitates learning through modern information retrieval systems.
WorldKG: A World-Scale Geographic Knowledge Graph
We describe the WorldKG knowledge graph, including its ontology that builds the semantic dataset backbone, the extraction procedure of the ontology and geographic entities from OpenStreetMap, and the methods to enhance entity annotation.
Real-time Human-Centric Segmentation for Complex Video Scenes
To alleviate this problem, we propose a mechanism named Inner Center Sampling to improve the accuracy of instance segmentation.
Ranked #4 on
Human Instance Segmentation
on OCHuman
PoseDet: Fast Multi-Person Pose Estimation Using Pose Embedding
This simple framework achieves an unprecedented speed and a competitive accuracy on the COCO benchmark compared with state-of-the-art methods.
Predicting Knowledge Gain during Web Search based on Multimedia Resource Consumption
Related work in this field, also called search as learning, has focused on behavioral or text resource features to predict learning outcome and knowledge gain.
TweetsCOV19 -- A Knowledge Base of Semantically Annotated Tweets about the COVID-19 Pandemic
Publicly available social media archives facilitate research in the social sciences and provide corpora for training and testing a wide range of machine learning and natural language processing methods.
