Search Results for author:
Found 23 papers, 7 papers with code
EA-RAS: Towards Efficient and Accurate End-to-End Reconstruction of Anatomical Skeleton
In this work, we also develop a progressive training strategy and integrated it with an enhanced optimization process, enabling the network to obtain initial weights using only a small skin dataset and achieve self-supervision in skeleton reconstruction.
Cross-Modal Spherical Aggregation for Weakly Supervised Remote Sensing Shadow Removal
To fill this gap, we propose a weakly supervised shadow removal network with a spherical feature space, dubbed S2-ShadowNet, to explore the best of both worlds for visible and infrared modalities.
OmniHands: Towards Robust 4D Hand Mesh Recovery via A Versatile Transformer
The results on in-the-wild videos and real-world scenarios demonstrate the superior performances of our approach for interactive hand reconstruction.
LASIL: Learner-Aware Supervised Imitation Learning For Long-term Microscopic Traffic Simulation
Due to the covariate shift issue, existing imitation learning-based simulators often fail to generate stable long-term simulations.
ProIn: Learning to Predict Trajectory Based on Progressive Interactions for Autonomous Driving
In this work, a progressive interaction network is proposed to enable the agent's feature to progressively focus on relevant maps, in order to better learn agents' feature representation capturing the relevant map constraints.
FusionAD: Multi-modality Fusion for Prediction and Planning Tasks of Autonomous Driving
Building a multi-modality multi-task neural network toward accurate and robust performance is a de-facto standard in perception task of autonomous driving.
Hierarchical Point Cloud Encoding and Decoding with Lightweight Self-Attention based Model
In this paper we present SA-CNN, a hierarchical and lightweight self-attention based encoding and decoding architecture for representation learning of point cloud data.
End-to-end Reinforcement Learning of Robotic Manipulation with Robust Keypoints Representation
The proposed method learns keypoints from camera images as the state representation, through a self-supervised autoencoder architecture.
Temporal Sentence Grounding in Videos: A Survey and Future Directions
Temporal sentence grounding in videos (TSGV), \aka natural language video localization (NLVL) or video moment retrieval (VMR), aims to retrieve a temporal moment that semantically corresponds to a language query from an untrimmed video.
Towards Debiasing Temporal Sentence Grounding in Video
In this paper, we propose two debiasing strategies, data debiasing and model debiasing, to "force" a TSGV model to capture cross-modal interactions.
Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee
The growing literature of Federated Learning (FL) has recently inspired Federated Reinforcement Learning (FRL) to encourage multiple agents to federatively build a better decision-making policy without sharing raw trajectories.
Domain Generalization for Vision-based Driving Trajectory Generation
In this paper, we propose a domain generalization method for vision-based driving trajectory generation for autonomous vehicles in urban environments, which can be seen as a solution to extend the Invariant Risk Minimization (IRM) method in complex problems.
Parallel Attention Network with Sequence Matching for Video Grounding
In this work, we propose a Parallel Attention Network with Sequence matching (SeqPAN) to address the challenges in this task: multi-modal representation learning, and target moment boundary prediction.
Video Corpus Moment Retrieval with Contrastive Learning
We adopt the first approach and introduce two contrastive learning objectives to refine video encoder and text encoder to learn video and text representations separately but with better alignment for VCMR.
Natural Language Video Localization: A Revisit in Span-based Question Answering Framework
Our study suggests that the span-based QA framework is an effective strategy to solve the NLVL problem.
Context Modeling with Evidence Filter for Multiple Choice Question Answering
In addition to the effective reduction of human efforts of our approach compared, through extensive experiments on OpenbookQA, we show that the proposed approach outperforms the models that use the same backbone and more training data; and our parameter analysis also demonstrates the interpretability of our approach.
KOVIS: Keypoint-based Visual Servoing with Zero-Shot Sim-to-Real Transfer for Robotics Manipulation
We train the deep neural network only in the simulated environment; and the trained model could be directly used for real-world visual servoing tasks.
Span-based Localizing Network for Natural Language Video Localization
Given an untrimmed video and a text query, natural language video localization (NLVL) is to locate a matching span from the video that semantically corresponds to the query.
Feature Super-Resolution Based Facial Expression Recognition for Multi-scale Low-Resolution Faces
The main cause of this problem is the loss of discriminative feature due to reduced resolution.
Facial Expression Recognition
Facial Expression Recognition (FER)
+4
RoboCoDraw: Robotic Avatar Drawing with GAN-based Style Transfer and Time-efficient Path Optimization
The proposed RoboCoDraw system takes a real human face image as input, converts it to a stylized avatar, then draws it with a robotic arm.
Robotics Graphics
Efficient Robotic Task Generalization Using Deep Model Fusion Reinforcement Learning
The proposed method is able to efficiently generalize the previously learned task by model fusion to solve the environment adaptation problem.
6D Pose Estimation with Correlation Fusion
To our best knowledge, this is the first work to explore effective intra- and inter-modality fusion in 6D pose estimation.
Coverage Path Planning using Path Primitive Sampling and Primitive Coverage Graph for Visual Inspection
In this paper, we propose a novel planning method to directly sample and plan the inspection path for a camera-equipped UAV to acquire visual and geometric information of the target structures as a video stream setting in complex 3D environment.
