2 citations · 6 across the 28 of their papers we have counts for
13 papers · 1 filter
FlashWorld: High-quality 3D Scene Generation within Seconds
Xinyang Li, Tengfei Wang, Zixiao Gu +3
We propose FlashWorld, a generative model that produces 3D scenes from a single image or text prompt in seconds, 10~100 faster than previous works while possessing superior…
SCOUT: Semi-supervised Camouflaged Object Detection by Utilizing Text and Adaptive Data Selection
Weiqi Yan, Lvhai Chen, Shengchuan Zhang +2
The difficulty of pixel-level annotation has significantly hindered the development of the Camouflaged Object Detection (COD) field. To save on annotation costs, previous works lev…
XSpecMesh: Quality-Preserving Auto-Regressive Mesh Generation Acceleration via Multi-Head Speculative Decoding
Dian Chen, Yansong Qu, Xinyang Li +2
Current auto-regressive models can generate high-quality, topologically precise meshes; however, they necessitate thousands-or even tens of thousands-of next-token predictions duri…
Generate Aligned Anomaly: Region-Guided Few-Shot Anomaly Image-Mask Pair Synthesis for Industrial Inspection
Yilin Lu, Jianghang Lin, Linhuang Xie +5
Anomaly inspection plays a vital role in industrial manufacturing, but the scarcity of anomaly samples significantly limits the effectiveness of existing methods in tasks such as l…
Inter2Former: Dynamic Hybrid Attention for Efficient High-Precision Interactive
You Huang, Lichao Chen, Jiayi Ji +3
Interactive segmentation (IS) improves annotation efficiency by segmenting target regions from user prompts, with widespread applications in real-world scenarios. Current approache…
UCOD-DPL: Unsupervised Camouflaged Object Detection via Dynamic Pseudo-label Learning
Weiqi Yan, Lvhai Chen, Huaijia Kou +3
Unsupervised Camoflaged Object Detection (UCOD) has gained attention since it doesn't need to rely on extensive pixel-level labels. Existing UCOD methods typically generate pseudo-…
What You Perceive Is What You Conceive: A Cognition-Inspired Framework for Open Vocabulary Image Segmentation
Jianghang Lin, Yue Hu, Jiangtao Shen +4
Open vocabulary image segmentation tackles the challenge of recognizing dynamically adjustable, predefined novel categories at inference time by leveraging vision-language alignmen…
Pseudo-Label Quality Decoupling and Correction for Semi-Supervised Instance Segmentation
Jianghang Lin, Yilin Lu, Yunhang Shen +4
Semi-Supervised Instance Segmentation (SSIS) involves classifying and grouping image pixels into distinct object instances using limited labeled data. This learning paradigm usuall…
SynergyAmodal: Deocclude Anything with Text Control
Xinyang Li, Chengjie Yi, Jiawei Lai +4
Image deocclusion (or amodal completion) aims to recover the invisible regions (\ie, shape and appearance) of occluded instances in images. Despite recent advances, the scarcity of…
Training-Free Hierarchical Scene Understanding for Gaussian Splatting with Superpoint Graphs
Shaohui Dai, Yansong Qu, Zheyan Li +3
Bridging natural language and 3D geometry is a crucial step toward flexible, language-driven scene understanding. While recent advances in 3D Gaussian Splatting (3DGS) have enabled…
BUFF: Bayesian Uncertainty Guided Diffusion Probabilistic Model for Single Image Super-Resolution
Zihao He, Shengchuan Zhang, Runze Hu +2
Super-resolution (SR) techniques are critical for enhancing image quality, particularly in scenarios where high-resolution imagery is essential yet limited by hardware constraints.…
Evolving High-Quality Rendering and Reconstruction in a Unified Framework with Contribution-Adaptive Regularization
You Shen, Zhipeng Zhang, Xinyang Li +4
Representing 3D scenes from multiview images is a core challenge in computer vision and graphics, which requires both precise rendering and accurate reconstruction. Recently, 3D Ga…
Drag Your Gaussian: Effective Drag-Based Editing with Score Distillation for 3D Gaussian Splatting
Yansong Qu, Dian Chen, Xinyang Li +4
Recent advancements in 3D scene editing have been propelled by the rapid development of generative models. Existing methods typically utilize generative models to perform text-guid…