6 citations · 6 across the 1 of their papers we have counts for
6 papers · 1 filter
Towards Reliable Advertising Image Generation Using Human Feedback
Zhenbang Du, Wei Feng, Haohan Wang +10
In the e-commerce realm, compelling advertising images are pivotal for attracting customer attention. While generative models automate image generation, they often produce substand…
The Devil is in the Edges: Monocular Depth Estimation with Edge-aware Consistency Fusion
Pengzhi Li, Yikang Ding, Haohan Wang +2
This paper presents a novel monocular depth estimation method, named ECFNet, for estimating high-quality monocular depth with clear edges and valid overall structure from a single…
Beyond Finite Data: Towards Data-free Out-of-distribution Generalization via Extrapolation
Yijiang Li, Sucheng Ren, Weipeng Deng +4
Out-of-distribution (OOD) generalization is a favorable yet challenging property for deep neural networks. The core challenges lie in the limited availability of source domains tha…
A Sentence Speaks a Thousand Images: Domain Generalization through Distilling CLIP with Language Guidance
Zeyi Huang, Andy Zhou, Zijian Lin +3
Domain generalization studies the problem of training a model with samples from several domains (or distributions) and then testing the model with samples from a new, unseen domain…
Calibrated Teacher for Sparsely Annotated Object Detection
Haohan Wang, Liang Liu, Boshen Zhang +6
Fully supervised object detection requires training images in which all instances are annotated. This is actually impractical due to the high labor and time costs and the unavoidab…
Iterative Few-shot Semantic Segmentation from Image Label Text
Haohan Wang, Liang Liu, Wuhao Zhang +5
Few-shot semantic segmentation aims to learn to segment unseen class objects with the guidance of only a few support images. Most previous methods rely on the pixel-level label of…