163 citations · 576 across the 33 of their papers we have counts for
33 papers
Fitting Unknown Number of Hyperplanes with Manifold Optimization
Zhiqin Cheng, Yu Zhan, Mingjin Zhang +2
Fitting an unknown number of hyperplanes to data is a fundamental yet challenging problem in machine learning, characterized by its non-convexity, non-differentiability, and unknow…
SkiP: When to Skip and When to Refine for Efficient Robot Manipulation
Mingtong Dai, Guanqi Peng, Yongjie Bai +5
Previous imitation learning policies predict future actions at every control step, whether in smooth motion phases or precise, contact-rich operation phases. This uniform treatment…
GraspView: Active Perception Scoring and Best-View Optimization for Robotic Grasping in Cluttered Environments
Shenglin Wang, Mingtong Dai, Jingxuan Su +4
Robotic grasping is a fundamental capability for autonomous manipulation, yet remains highly challenging in cluttered environments where occlusion, poor perception quality, and inc…
RoVer: Robot Reward Model as Test-Time Verifier for Vision-Language-Action Model
Mingtong Dai, Lingbo Liu, Yongjie Bai +6
Vision-Language-Action (VLA) models have become a prominent paradigm for embodied intelligence, yet further performance improvements typically rely on scaling up training data and…
Learning to See and Act: Task-Aware Virtual View Exploration for Robotic Manipulation
Yongjie Bai, Zhouxia Wang, Yang Liu +8
Recent vision-language-action (VLA) models for multi-task robot manipulation often rely on fixed camera setups and shared visual encoders, which limit their performance under occlu…
Spatio-Temporal Graph Neural Point Process for Traffic Congestion Event Prediction
Guangyin Jin, Lingbo Liu, Fuxian Li +1
Traffic congestion event prediction is an important yet challenging task in intelligent transportation systems. Many existing works about traffic prediction integrate various tempo…
SQLNet: Scale-Modulated Query and Localization Network for Few-Shot Class-Agnostic Counting
Hefeng Wu, Yandong Chen, Lingbo Liu +3
The class-agnostic counting (CAC) task has recently been proposed to solve the problem of counting all objects of an arbitrary class with several exemplars given in the input image…
DenseLight: Efficient Control for Large-scale Traffic Signals with Dense Feedback
Junfan Lin, Yuying Zhu, Lingbo Liu +3
Traffic Signal Control (TSC) aims to reduce the average travel time of vehicles in a road network, which in turn enhances fuel utilization efficiency, air quality, and road safety,…
Long-term Wind Power Forecasting with Hierarchical Spatial-Temporal Transformer
Yang Zhang, Lingbo Liu, Xinyu Xiong +3
Wind power is attracting increasing attention around the world due to its renewable, pollution-free, and other advantages. However, safely and stably integrating the high permeabil…
Urban Regional Function Guided Traffic Flow Prediction
Kuo Wang, Lingbo Liu, Yang Liu +3
The prediction of traffic flow is a challenging yet crucial problem in spatial-temporal analysis, which has recently gained increasing interest. In addition to spatial-temporal cor…
Being Comes from Not-being: Open-vocabulary Text-to-Motion Generation with Wordless Training
Junfan Lin, Jianlong Chang, Lingbo Liu +4
Text-to-motion generation is an emerging and challenging problem, which aims to synthesize motion with the same semantics as the input text. However, due to the lack of diverse lab…
Prompt-Matched Semantic Segmentation
Lingbo Liu, Jianlong Chang, Bruce X. B. Yu +3
The objective of this work is to explore how to effectively and efficiently adapt pre-trained visual foundation models to various downstream tasks of semantic segmentation. Previou…
Heterogeneous Semantic Transfer for Multi-label Recognition with Partial Labels
Tianshui Chen, Tao Pu, Lingbo Liu +3
Multi-label image recognition with partial labels (MLR-PL), in which some labels are known while others are unknown for each image, may greatly reduce the cost of annotation and th…
Unconstrained Face Sketch Synthesis via Perception-Adaptive Network and A New Benchmark
Lin Nie, Lingbo Liu, Zhengtao Wu +1
Face sketch generation has attracted much attention in the field of visual computing. However, existing methods either are limited to constrained conditions or heavily rely on vari…
TCGL: Temporal Contrastive Graph for Self-supervised Video Representation Learning
Yang Liu, Keze Wang, Lingbo Liu +2
Video self-supervised learning is a challenging task, which requires significant expressive power from the model to leverage rich spatial-temporal knowledge and generate effective…
Aerial Images Meet Crowdsourced Trajectories: A New Approach to Robust Road Extraction
Lingbo Liu, Zewei Yang, Guanbin Li +3
Land remote sensing analysis is a crucial research in earth science. In this work, we focus on a challenging task of land analysis, i.e., automatic extraction of traffic roads from…
Road Network Guided Fine-Grained Urban Traffic Flow Inference
Lingbo Liu, Mengmeng Liu, Guanbin Li +3
Accurate inference of fine-grained traffic flow from coarse-grained one is an emerging yet crucial problem, which can help greatly reduce the number of the required traffic monitor…
GroupFormer: Group Activity Recognition with Clustered Spatial-Temporal Transformer
Shuaicheng Li, Qianggang Cao, Lingbo Liu +4
Group activity recognition is a crucial yet challenging problem, whose core lies in fully exploring spatial-temporal interactions among individuals and generating reasonable group…
Video Crowd Localization with Multi-focus Gaussian Neighborhood Attention and a Large-Scale Benchmark
Haopeng Li, Lingbo Liu, Kunlin Yang +5
Video crowd localization is a crucial yet challenging task, which aims to estimate exact locations of human heads in the given crowded videos. To model spatial-temporal dependencie…
Online Metro Origin-Destination Prediction via Heterogeneous Information Aggregation
Lingbo Liu, Yuying Zhu, Guanbin Li +3
Metro origin-destination prediction is a crucial yet challenging time-series analysis task in intelligent transportation systems, which aims to accurately forecast two specific typ…
GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning
Jiaqi Chen, Jianheng Tang, Jinghui Qin +4
Automatic math problem solving has recently attracted increasing attention as a long-standing AI benchmark. In this paper, we focus on solving geometric problems, which requires a…
Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting
Lingbo Liu, Jiaqi Chen, Hefeng Wu +3
Crowd counting is a fundamental yet challenging task, which desires rich information to generate pixel-wise crowd density maps. However, most previous methods only used the limited…
Cross-Domain Facial Expression Recognition: A Unified Evaluation Benchmark and Adversarial Graph Learning
Tianshui Chen, Tao Pu, Hefeng Wu +3
To address the problem of data inconsistencies among different facial expression recognition (FER) datasets, many cross-domain FER methods (CD-FERs) have been extensively devised i…
Efficient Crowd Counting via Structured Knowledge Transfer
Lingbo Liu, Jiaqi Chen, Hefeng Wu +3
Crowd counting is an application-oriented task and its inference efficiency is crucial for real-world applications. However, most previous works relied on heavy backbone networks a…