most citedDomain Adaptation via Prompt Learning

9 citations · 20 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2024

Structured Click Control in Transformer-based Interactive Segmentation

Long Xu, Yongquan Chen, Rui Huang +2

Click-point-based interactive segmentation has received widespread attention due to its efficiency. However, it's hard for existing algorithms to obtain precise and robust response…

cs.CL20231 cited

Producing Usable Taxonomies Cheaply and Rapidly at Pinterest Using Discovered Dynamic -Topics

Abhijit Mahabal, Jiyun Luo, Rui Huang +2

Creating a taxonomy of interests is expensive and human-effort intensive: not only do we need to identify nodes and interconnect them, in order to use the taxonomy, we must also co…

cs.CV20231 cited

Joint Representation Learning for Text and 3D Point Cloud

Rui Huang, Xuran Pan, Henry Zheng +4

Recent advancements in vision-language pre-training (e.g. CLIP) have shown that vision models can benefit from language supervision. While many models using language modality have…

cs.CV20226 cited

RenderNet: Visual Relocalization Using Virtual Viewpoints in Large-Scale Indoor Environments

Jiahui Zhang, Shitao Tang, Kejie Qiu +6

Visual relocalization has been a widely discussed problem in 3D vision: given a pre-constructed 3D visual map, the 6 DoF (Degrees-of-Freedom) pose of a query image is estimated. Re…

cs.CV20221 cited

Deep Semantic Statistics Matching (D2SM) Denoising Network

Kangfu Mei, Vishal M. Patel, Rui Huang

The ultimate aim of image restoration like denoising is to find an exact correlation between the noisy and clear image domains. But the optimization of end-to-end denoising learnin…

cs.CV20229 cited

Domain Adaptation via Prompt Learning

Chunjiang Ge, Rui Huang, Mixue Xie +4

Unsupervised domain adaption (UDA) aims to adapt models learned from a well-annotated source domain to a target domain, where only unlabeled samples are given. Current UDA approach…