297 citations · 832 across the 37 of their papers we have counts for
40 papers
Robust Driving Policy Learning with Guided Meta Reinforcement Learning
Kanghoon Lee, Jiachen Li, David Isele +3
Although deep reinforcement learning (DRL) has shown promising results for autonomous navigation in interactive traffic scenarios, existing work typically adopts a fixed behavior p…
Pedestrian Crossing Action Recognition and Trajectory Prediction with 3D Human Keypoints
Jiachen Li, Xinwei Shi, Feiyu Chen +9
Accurate understanding and prediction of human behaviors are critical prerequisites for autonomous vehicles, especially in highly dynamic and interactive scenarios such as intersec…
Learning Physical Dynamics with Subequivariant Graph Neural Networks
Jiaqi Han, Wenbing Huang, Hengbo Ma +3
Graph Neural Networks (GNNs) have become a prevailing tool for learning physical dynamics. However, they still encounter several challenges: 1) Physical laws abide by symmetry, whi…
DRAMA: Joint Risk Localization and Captioning in Driving
Srikanth Malla, Chiho Choi, Isht Dwivedi +2
Considering the functionality of situational awareness in safety-critical automation systems, the perception of risk in driving scenes and its explainability is of particular impor…
Dynamics-Aware Spatiotemporal Occupancy Prediction in Urban Environments
Maneekwan Toyungyernsub, Esen Yel, Jiachen Li +1
Detection and segmentation of moving obstacles, along with prediction of the future occupancy states of the local environment, are essential for autonomous vehicles to proactively…
EvolveHypergraph: Group-Aware Dynamic Relational Reasoning for Trajectory Prediction
Jiachen Li, Chuanbo Hua, Jinkyoo Park +3
While the modeling of pair-wise relations has been widely studied in multi-agent interacting systems, its ability to capture higher-level and larger-scale group-wise activities is…
Interaction Modeling with Multiplex Attention
Fan-Yun Sun, Isaac Kauvar, Ruohan Zhang +4
Modeling multi-agent systems requires understanding how agents interact. Such systems are often difficult to model because they can involve a variety of types of interactions that…
Symbolic Expression Transformer: A Computer Vision Approach for Symbolic Regression
Jiachen Li, Ye Yuan, Hong-Bin Shen
Symbolic Regression (SR) is a type of regression analysis to automatically find the mathematical expression that best fits the data. Currently, SR still basically relies on various…
ConvNeXt-backbone HoVerNet for nuclei segmentation and classification
Jiachen Li, Chixin Wang, Banban Huang +1
This manuscript gives a brief description of the algorithm used to participate in CoNIC Challenge 2022. After the baseline was made available, we follow the method in it and replac…
Important Object Identification with Semi-Supervised Learning for Autonomous Driving
Jiachen Li, Haiming Gang, Hengbo Ma +2
Accurate identification of important objects in the scene is a prerequisite for safe and high-quality decision making and motion planning of intelligent agents (e.g., autonomous ve…
Offline-Online Associated Camera-Aware Proxies for Unsupervised Person Re-identification
Menglin Wang, Jiachen Li, Baisheng Lai +2
Recently, unsupervised person re-identification (Re-ID) has received increasing research attention due to its potential for label-free applications. A promising way to address unsu…
SeMask: Semantically Masked Transformers for Semantic Segmentation
Jitesh Jain, Anukriti Singh, Nikita Orlov +4
Finetuning a pretrained backbone in the encoder part of an image transformer network has been the traditional approach for the semantic segmentation task. However, such an approach…
SS-MAIL: Self-Supervised Multi-Agent Imitation Learning
Akshay Dharmavaram, Tejus Gupta, Jiachen Li +1
The current landscape of multi-agent expert imitation is broadly dominated by two families of algorithms - Behavioral Cloning (BC) and Adversarial Imitation Learning (AIL). BC appr…
ConvMLP: Hierarchical Convolutional MLPs for Vision
Jiachen Li, Ali Hassani, Steven Walton +1
MLP-based architectures, which consist of a sequence of consecutive multi-layer perceptron blocks, have recently been found to reach comparable results to convolutional and transfo…
LOKI: Long Term and Key Intentions for Trajectory Prediction
Harshayu Girase, Haiming Gang, Srikanth Malla +4
Recent advances in trajectory prediction have shown that explicit reasoning about agents' intent is important to accurately forecast their motion. However, the current research act…
Grouptron: Dynamic Multi-Scale Graph Convolutional Networks for Group-Aware Dense Crowd Trajectory Forecasting
Rui Zhou, Hongyu Zhou, Huidong Gao +3
Accurate, long-term forecasting of pedestrian trajectories in highly dynamic and interactive scenes is a long-standing challenge. Recent advances in using data-driven approaches ha…
RAIN: Reinforced Hybrid Attention Inference Network for Motion Forecasting
Jiachen Li, Fan Yang, Hengbo Ma +3
Motion forecasting plays a significant role in various domains (e.g., autonomous driving, human-robot interaction), which aims to predict future motion sequences given a set of his…
Orientation-Aware Planning for Parallel Task Execution of Omni-Directional Mobile Robot
Cheng Gong, Zirui Li, Xingyu Zhou +3
Omni-directional mobile robot (OMR) systems have been very popular in academia and industry for their superb maneuverability and flexibility. Yet their potential has not been fully…
Autonomous Driving Strategies at Intersections: Scenarios, State-of-the-Art, and Future Outlooks
Lianzhen Wei, Zirui Li, Jianwei Gong +2
Due to the complex and dynamic character of intersection scenarios, the autonomous driving strategy at intersections has been a difficult problem and a hot point in the research of…
MSN: Efficient Online Mask Selection Network for Video Instance Segmentation
Vidit Goel, Jiachen Li, Shubhika Garg +2
In this work we present a novel solution for Video Instance Segmentation(VIS), that is automatically generating instance level segmentation masks along with object class and tracki…
Spectral Temporal Graph Neural Network for Trajectory Prediction
Defu Cao, Jiachen Li, Hengbo Ma +1
An effective understanding of the contextual environment and accurate motion forecasting of surrounding agents is crucial for the development of autonomous vehicles and social mobi…
RSCA: Real-time Segmentation-based Context-Aware Scene Text Detection
Jiachen Li, Yuan Lin, Rongrong Liu +2
Segmentation-based scene text detection methods have been widely adopted for arbitrary-shaped text detection recently, since they make accurate pixel-level predictions on curved te…
Pseudo-IoU: Improving Label Assignment in Anchor-Free Object Detection
Jiachen Li, Bowen Cheng, Rogerio Feris +4
Current anchor-free object detectors are quite simple and effective yet lack accurate label assignment methods, which limits their potential in competing with classic anchor-based…
Escaping the Big Data Paradigm with Compact Transformers
Ali Hassani, Steven Walton, Nikhil Shah +3
With the rise of Transformers as the standard for language processing, and their advancements in computer vision, there has been a corresponding growth in parameter size and amount…