29 citations · 92 across the 24 of their papers we have counts for
9 papers · 1 filter
TransPose: 6D Object Pose Estimation with Geometry-Aware Transformer
Xiao Lin, Deming Wang, Guangliang Zhou +2
Estimating the 6D object pose is an essential task in many applications. Due to the lack of depth information, existing RGB-based methods are sensitive to occlusion and illuminatio…
InstructDET: Diversifying Referring Object Detection with Generalized Instructions
Ronghao Dang, Jiangyan Feng, Haodong Zhang +8
We propose InstructDET, a data-centric method for referring object detection (ROD) that localizes target objects based on user instructions. While deriving from referring expressio…
Adaptive Denoising-Enhanced LiDAR Odometry for Degeneration Resilience in Diverse Terrains
Mazeyu Ji, Wenbo Shi, Yujie Cui +2
The flexibility of Simultaneous Localization and Mapping (SLAM) algorithms in various environments has consistently been a significant challenge. To address the issue of LiDAR odom…
Fine-Grained Spatiotemporal Motion Alignment for Contrastive Video Representation Learning
Minghao Zhu, Xiao Lin, Ronghao Dang +2
As the most essential property in a video, motion information is critical to a robust and generalized video representation. To inject motion dynamics, recent works have adopted fra…
A Dual Semantic-Aware Recurrent Global-Adaptive Network For Vision-and-Language Navigation
Liuyi Wang, Zongtao He, Jiagui Tang +4
Vision-and-Language Navigation (VLN) is a realistic but challenging task that requires an agent to locate the target region using verbal and visual cues. While significant advancem…
PASTS: Progress-Aware Spatio-Temporal Transformer Speaker For Vision-and-Language Navigation
Liuyi Wang, Chengju Liu, Zongtao He +4
Vision-and-language navigation (VLN) is a crucial but challenging cross-modal navigation task. One powerful technique to enhance the generalization performance in VLN is the use of…
MLANet: Multi-Level Attention Network with Sub-instruction for Continuous Vision-and-Language Navigation
Zongtao He, Liuyi Wang, Shu Li +3
Vision-and-Language Navigation (VLN) aims to develop intelligent agents to navigate in unseen environments only through language and vision supervision. In the recently proposed co…
Multiple Thinking Achieving Meta-Ability Decoupling for Object Navigation
Ronghao Dang, Lu Chen, Liuyi Wang +3
We propose a meta-ability decoupling (MAD) paradigm, which brings together various object navigation methods in an architecture system, allowing them to mutually enhance each other…
Meta-Learning Adaptive Loss Functions
Christian Raymond, Qi Chen, Bing Xue +1
Loss function learning is a new meta-learning paradigm that aims to automate the essential task of designing a loss function for a machine learning model. Existing techniques for l…