Search Results for author:
Found 14 papers, 3 papers with code
QuadBEV: An Efficient Quadruple-Task Perception Framework via Bird's-Eye-View Representation
Bird's-Eye-View (BEV) perception has become a vital component of autonomous driving systems due to its ability to integrate multiple sensor inputs into a unified representation, enhancing performance in various downstream tasks.
Learning Content-Aware Multi-Modal Joint Input Pruning via Bird's-Eye-View Representation
In the landscape of autonomous driving, Bird's-Eye-View (BEV) representation has recently garnered substantial academic attention, serving as a transformative framework for the fusion of multi-modal sensor inputs.
Transferability of Representations Learned using Supervised Contrastive Learning Trained on a Multi-Domain Dataset
Contrastive learning has shown to learn better quality representations than models trained using cross-entropy loss.
DeformToon3D: Deformable 3D Toonification from Neural Radiance Fields
In this paper, we address the challenging problem of 3D toonification, which involves transferring the style of an artistic domain onto a target 3D face with stylized geometry and texture.
DeformToon3D: Deformable Neural Radiance Fields for 3D Toonification
In this paper, we address the challenging problem of 3D toonification, which involves transferring the style of an artistic domain onto a target 3D face with stylized geometry and texture.
Abductive Action Inference
In this paper, we introduce a novel research task known as "abductive action inference" which addresses the question of which actions were executed by a human to reach a specific state shown in a single snapshot.
Monocular 3D Object Reconstruction with GAN Inversion
Reconstruction is achieved by searching for a latent space in the 3D GAN that best resembles the target mesh in accordance with the single view observation.
NSGZero: Efficiently Learning Non-Exploitable Policy in Large-Scale Network Security Games with Neural Monte Carlo Tree Search
Second, we enable neural MCTS with decentralized control, making NSGZero applicable to NSGs with many resources.
MeshInversion: 3D textured mesh reconstruction with generative prior
Reconstruction is achieved by searching for a latent space in the 3D GAN that best resembles the target mesh in accordance with the single view observation.
Mis-spoke or mis-lead: Achieving Robustness in Multi-Agent Communicative Reinforcement Learning
Empirical results demonstrate that many state-of-the-art MACRL methods are vulnerable to message attacks, and our method can significantly improve their robustness.
Multi-agent Reinforcement Learning
reinforcement-learning
+2
Solving Large-Scale Extensive-Form Network Security Games via Neural Fictitious Self-Play
Securing networked infrastructures is important in the real world.
Unsupervised 3D Shape Completion through GAN Inversion
In contrast to previous fully supervised approaches, in this paper we present ShapeInversion, which introduces Generative Adversarial Network (GAN) inversion to shape completion for the first time.
Self-Organizing Map assisted Deep Autoencoding Gaussian Mixture Model for Intrusion Detection
In this paper, we propose a self-organizing map assisted deep autoencoding Gaussian mixture model (SOMDAGMM) supplemented with well-preserved input space topology for more accurate network intrusion detection.
MessyTable: Instance Association in Multiple Camera Views
We present an interesting and challenging dataset that features a large number of scenes with messy tables captured from multiple camera views.
