Search Results for author:
Found 15 papers, 4 papers with code
Empowering Embodied Visual Tracking with Visual Foundation Models and Offline RL
We evaluate our tracker on several high-fidelity environments with challenging situations, such as distraction and occlusion.
Learning based 2D Irregular Shape Packing
2D irregular shape packing is a necessary step to arrange UV patches of a 3D model within a texture atlas for memory-efficient appearance rendering in computer graphics.
Killing Two Birds with One Stone: Quantization Achieves Privacy in Distributed Learning
Communication efficiency and privacy protection are two critical issues in distributed machine learning.
HiVT: Hierarchical Vector Transformer for Multi-Agent Motion Prediction
To tackle this challenge, we propose Hierarchical Vector Transformer (HiVT) for fast and accurate multi-agent motion prediction.
Ranked #24 on
Motion Forecasting
on Argoverse CVPR 2020
A Generative Car-following Model Conditioned On Driving Styles
Car-following (CF) modeling, an essential component in simulating human CF behaviors, has attracted increasing research interest in the past decades.
Detecting and Identifying Optical Signal Attacks on Autonomous Driving Systems
In our study, we use real data sets and the state-of-the-art machine learning model to evaluate our attack detection scheme and the results confirm the effectiveness of our detection method.
On the Difficulty of Generalizing Reinforcement Learning Framework for Combinatorial Optimization
Combinatorial optimization problems (COPs) on the graph with real-life applications are canonical challenges in Computer Science.
Evaluating Adversarial Attacks on Driving Safety in Vision-Based Autonomous Vehicles
In this paper, we investigate the impact of two primary types of adversarial attacks, perturbation attacks and patch attacks, on the driving safety of vision-based autonomous vehicles rather than the detection precision of deep learning models.
DiffCloth: Differentiable Cloth Simulation with Dry Frictional Contact
This work presents a differentiable cloth simulator whose additional gradient information facilitates cloth-related applications.
Addressing the Vulnerability of NMT in Input Perturbations
Neural Machine Translation (NMT) has achieved significant breakthrough in performance but is known to suffer vulnerability to input perturbations.
DiffAqua: A Differentiable Computational Design Pipeline for Soft Underwater Swimmers with Shape Interpolation
The computational design of soft underwater swimmers is challenging because of the high degrees of freedom in soft-body modeling.
DiffPD: Differentiable Projective Dynamics
Inspired by Projective Dynamics (PD), we present Differentiable Projective Dynamics (DiffPD), an efficient differentiable soft-body simulator based on PD with implicit time integration.
Sentiment Aware Neural Machine Translation
We conducted tests with both sentiment and non-sentiment bearing contexts to examine the effectiveness of our methods.
D3PG: Deep Differentiable Deterministic Policy Gradients
Over the last decade, two competing control strategies have emerged for solving complex control tasks with high efficacy.
Plug and Play! A Simple, Universal Model for Energy Disaggregation
Energy disaggregation is to discover the energy consumption of individual appliances from their aggregated energy values.
