36 citations · 60 across the 14 of their papers we have counts for
9 papers · 1 filter
P2DNav: Panorama-to-Downview Reasoning for Zero-shot Vision-and-Language Navigation
Kai Sheng, Liuyi Wang, Haojie Dai +5
Vision-and-language navigation (VLN) requires an embodied agent to ground natural-language instructions into executable navigation actions in unseen environments. Existing zero-sho…
MAGIC: Meta-Ability Guided Interactive Chain-of-Distillation for Effective-and-Efficient Vision-and-Language Navigation
Liuyi Wang, Zongtao He, Mengjiao Shen +3
Despite the remarkable developments of recent large models in Embodied Artificial Intelligence (E-AI), their integration into robotics is hampered by their excessive parameter size…
DCPI-Depth: Explicitly Infusing Dense Correspondence Prior to Unsupervised Monocular Depth Estimation
Mengtan Zhang, Yi Feng, Qijun Chen +1
There has been a recent surge of interest in learning to perceive depth from monocular videos in an unsupervised fashion. A key challenge in this field is achieving robust and accu…
Playing to Vision Foundation Model's Strengths in Stereo Matching
Chuang-Wei Liu, Qijun Chen, Rui Fan
Stereo matching has become a key technique for 3D environment perception in intelligent vehicles. For a considerable time, convolutional neural networks (CNNs) have remained the ma…
LIX: Implicitly Infusing Spatial Geometric Prior Knowledge into Visual Semantic Segmentation for Autonomous Driving
Sicen Guo, Ziwei Long, Zhiyuan Wu +3
Despite the impressive performance achieved by data-fusion networks with duplex encoders for visual semantic segmentation, they become ineffective when spatial geometric data are n…
SM-Net: Joint Learning of Semantic Segmentation and Stereo Matching for Autonomous Driving
Zhiyuan Wu, Yi Feng, Chuang-Wei Liu +3
Semantic segmentation and stereo matching are two essential components of 3D environmental perception systems for autonomous driving. Nevertheless, conventional approaches often ad…
E3CM: Epipolar-Constrained Cascade Correspondence Matching
Chenbo Zhou, Shuai Su, Qijun Chen +1
Accurate and robust correspondence matching is of utmost importance for various 3D computer vision tasks. However, traditional explicit programming-based methods often struggle to…
Revisiting Perspective Information for Efficient Crowd Counting
Miaojing Shi, Zhaohui Yang, Chao Xu +1
Crowd counting is the task of estimating people numbers in crowd images. Modern crowd counting methods employ deep neural networks to estimate crowd counts via crowd density regres…
Novel View Synthesis for Large-scale Scene using Adversarial Loss
Xiaochuan Yin, Henglai Wei, Penghong lin +2
Novel view synthesis aims to synthesize new images from different viewpoints of given images. Most of previous works focus on generating novel views of certain objects with a fixed…