activity
20162025
most citedPyramid Scene Parsing Network

312 citations · 1.5k across the 54 of their papers we have counts for

collaborators
Showing 2023Show all

16 papers · 1 filter

cs.CV2023★ 1 cited

Shrinking Class Space for Enhanced Certainty in Semi-Supervised Learning

Lihe Yang, Zhen Zhao, Lei Qi +3

Semi-supervised learning is attracting blooming attention, due to its success in combining unlabeled data. To mitigate potentially incorrect pseudo labels, recent frameworks mostly…

cs.CV2023★ 4 cited

Towards Large-scale 3D Representation Learning with Multi-dataset Point Prompt Training

Xiaoyang Wu, Zhuotao Tian, Xin Wen +4

The rapid advancement of deep learning models often attributes to their ability to leverage massive training data. In contrast, such privilege has not yet fully benefited 3D deep l…

cs.CV2023★ 6 cited

InsMapper: Exploring Inner-instance Information for Vectorized HD Mapping

Zhenhua Xu, Kwan-Yee. K. Wong, Hengshuang Zhao

Vectorized high-definition (HD) maps contain detailed information about surrounding road elements, which are crucial for various downstream tasks in modern autonomous vehicles, suc…

cs.CV2023★ 1 cited

GroupLane: End-to-End 3D Lane Detection with Channel-wise Grouping

Zhuoling Li, Chunrui Han, Zheng Ge +5

Efficiency is quite important for 3D lane detection due to practical deployment demand. In this work, we propose a simple, fast, and end-to-end detector that still maintains high d…

cs.CV2023★ 11 cited

AnyDoor: Zero-shot Object-level Image Customization

Xi Chen, Lianghua Huang, Yu Liu +3

This work presents AnyDoor, a diffusion-based image generator with the power to teleport target objects to new scenes at user-specified locations in a harmonious way. Instead of tu…

cs.CV2023★ 33 cited

SAM3D: Segment Anything in 3D Scenes

Yunhan Yang, Xiaoyang Wu, Tong He +2

In this work, we propose SAM3D, a novel framework that is able to predict masks in 3D point clouds by leveraging the Segment-Anything Model (SAM) in RGB images without further trai…

cs.CV2023★ 2 cited

OCBEV: Object-Centric BEV Transformer for Multi-View 3D Object Detection

Zhangyang Qi, Jiaqi Wang, Xiaoyang Wu +1

Multi-view 3D object detection is becoming popular in autonomous driving due to its high effectiveness and low cost. Most of the current state-of-the-art detectors follow the query…

cs.CV2023★ 3 cited

VoxelFormer: Bird's-Eye-View Feature Generation based on Dual-view Attention for Multi-view 3D Object Detection

Zhuoling Li, Chuanrui Zhang, Wei-Chiu Ma +5

In recent years, transformer-based detectors have demonstrated remarkable performance in 2D visual perception tasks. However, their performance in multi-view 3D object detection re…

cs.CV2023★ 4 cited

Detecting Everything in the Open World: Towards Universal Object Detection

Zhenyu Wang, Yali Li, Xi Chen +4

In this paper, we formally address universal object detection, which aims to detect every scene and predict every category. The dependence on human annotations, the limited visual…

cs.CV2023★ 2 cited

Masked Scene Contrast: A Scalable Framework for Unsupervised 3D Representation Learning

Xiaoyang Wu, Xin Wen, Xihui Liu +1

As a pioneering work, PointContrast conducts unsupervised 3D representation learning via leveraging contrastive learning over raw RGB-D frames and proves its effectiveness on vario…

cs.CV2023★ 6 cited

ScribbleSeg: Scribble-based Interactive Image Segmentation

Xi Chen, Yau Shing Jonathan Cheung, Ser-Nam Lim +1

Interactive segmentation enables users to extract masks by providing simple annotations to indicate the target, such as boxes, clicks, or scribbles. Among these interaction formats…

cs.CV2023★ 1 cited

GeoSpark: Sparking up Point Cloud Segmentation with Geometry Clue

Zhening Huang, Xiaoyang Wu, Hengshuang Zhao +4

Current point cloud segmentation architectures suffer from limited long-range feature modeling, as they mostly rely on aggregating information with local neighborhoods. Furthermore…

cs.CV2023★ 1 cited

Semantics-Aware Dynamic Localization and Refinement for Referring Image Segmentation

Zhao Yang, Jiaqi Wang, Yansong Tang +3

Referring image segmentation segments an image from a language expression. With the aim of producing high-quality masks, existing methods often adopt iterative learning approaches…

cs.CV2023★ 1 cited

Influencer Backdoor Attack on Semantic Segmentation

Haoheng Lan, Jindong Gu, Philip Torr +1

When a small number of poisoned samples are injected into the training dataset of a deep neural network, the network can be induced to exhibit malicious behavior during inferences,…

cs.CV2023★ 1 cited

Open-vocabulary Panoptic Segmentation with Embedding Modulation

Xi Chen, Shuang Li, Ser-Nam Lim +2

Open-vocabulary image segmentation is attracting increasing attention due to its critical applications in the real world. Traditional closed-vocabulary segmentation methods are not…

cs.CV2023★ 6 cited

PhysFormer++: Facial Video-based Physiological Measurement with SlowFast Temporal Difference Transformer

Zitong Yu, Yuming Shen, Jingang Shi +5

Remote photoplethysmography (rPPG), which aims at measuring heart activities and physiological signals from facial video without any contact, has great potential in many applicatio…