201 citations · 260 across the 11 of their papers we have counts for
11 papers
SEAL: SEmantic-Augmented Imitation Learning via Language Model
Chengyang Gu, Yuxin Pan, Haotian Bai +2
Hierarchical Imitation Learning (HIL) is a promising approach for tackling long-horizon decision-making tasks. While it is a challenging task due to the lack of detailed supervisor…
High-Fidelity Mask-free Neural Surface Reconstruction for Virtual Reality
Haotian Bai, Yize Chen, Lin Wang
Object-centric surface reconstruction from multi-view images is crucial in creating editable digital assets for AR/VR. Due to the lack of geometric constraints, existing methods, e…
PanDA: Towards Panoramic Depth Anything with Unlabeled Panoramas and Mobius Spatial Augmentation
Zidong Cao, Jinjing Zhu, Weiming Zhang +4
Recently, Depth Anything Models (DAMs) - a type of depth foundation models - have demonstrated impressive zero-shot capabilities across diverse perspective images. Despite its succ…
Hi-Map: Hierarchical Factorized Radiance Field for High-Fidelity Monocular Dense Mapping
Tongyan Hua, Haotian Bai, Zidong Cao +3
In this paper, we introduce Hi-Map, a novel monocular dense mapping approach based on Neural Radiance Field (NeRF). Hi-Map is exceptional in its capacity to achieve efficient and h…
Dynamic PlenOctree for Adaptive Sampling Refinement in Explicit NeRF
Haotian Bai, Yiqi Lin, Yize Chen +1
The explicit neural radiance field (NeRF) has gained considerable interest for its efficient training and fast inference capabilities, making it a promising direction such as virtu…
FMapping: Factorized Efficient Neural Field Mapping for Real-Time Dense RGB SLAM
Tongyan Hua, Haotian Bai, Zidong Cao +1
In this paper, we introduce FMapping, an efficient neural field mapping framework that facilitates the continuous estimation of a colorized point cloud map in real-time dense RGB S…
CompoNeRF: Text-guided Multi-object Compositional NeRF with Editable 3D Scene Layout
Haotian Bai, Yuanhuiyi Lyu, Lutao Jiang +4
Text-to-3D form plays a crucial role in creating editable 3D scenes for AR/VR. Recent advances have shown promise in merging neural radiance fields (NeRFs) with pre-trained diffusi…
Patch-Mix Transformer for Unsupervised Domain Adaptation: A Game Perspective
Jinjing Zhu, Haotian Bai, Lin Wang
Endeavors have been recently made to leverage the vision transformer (ViT) for the challenging unsupervised domain adaptation (UDA) task. They typically adopt the cross-attention i…
Weakly Supervised Object Localization via Transformer with Implicit Spatial Calibration
Haotian Bai, Ruimao Zhang, Jiong Wang +1
Weakly Supervised Object Localization (WSOL), which aims to localize objects by only using image-level labels, has attracted much attention because of its low annotation cost in re…
AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation
Yuanfeng Ji, Haotian Bai, Jie Yang +8
Despite the considerable progress in automatic abdominal multi-organ segmentation from CT/MRI scans in recent years, a comprehensive evaluation of the models' capabilities is hampe…
Deep Learning for Omnidirectional Vision: A Survey and New Perspectives
Hao Ai, Zidong Cao, Jinjing Zhu +3
Omnidirectional image (ODI) data is captured with a 360x180 field-of-view, which is much wider than the pinhole cameras and contains richer spatial information than the conventiona…