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20182026
most citedMMDetection: Open MMLab Detection Toolbox and Benchmark

794 citations · 2k across the 30 of their papers we have counts for

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30 papers · 1 filter

cs.CV2026

Cross-Layer Attentive Feature Upsampling for Low-latency Semantic Segmentation

Tianheng Cheng, Xinggang Wang, Junchao Liao +1

Semantic segmentation is a fundamental problem in computer vision and it requires high-resolution feature maps for dense prediction. Current coordinate-guided low-resolution featur…

cs.CV2025

LENS: Learning to Segment Anything with Unified Reinforced Reasoning

Lianghui Zhu, Bin Ouyang, Yuxuan Zhang +8

Text-prompted image segmentation enables fine-grained visual understanding and is critical for applications such as human-computer interaction and robotics. However, existing super…

cs.CV2025

Multimodal Mamba: Decoder-only Multimodal State Space Model via Quadratic to Linear Distillation

Bencheng Liao, Hongyuan Tao, Qian Zhang +5

Recent Multimodal Large Language Models (MLLMs) have achieved remarkable performance but face deployment challenges due to their quadratic computational complexity, growing Key-Val…

cs.CV2025

GroundingSuite: Measuring Complex Multi-Granular Pixel Grounding

Rui Hu, Lianghui Zhu, Yuxuan Zhang +7

Pixel grounding, encompassing tasks such as Referring Expression Segmentation (RES), has garnered considerable attention due to its immense potential for bridging the gap between v…

cs.CV2024

GaussTR: Foundation Model-Aligned Gaussian Transformer for Self-Supervised 3D Spatial Understanding

Haoyi Jiang, Liu Liu, Tianheng Cheng +5

3D Semantic Occupancy Prediction is fundamental for spatial understanding, yet existing approaches face challenges in scalability and generalization due to their reliance on extens…

cs.CV2024

Mask-Adapter: The Devil is in the Masks for Open-Vocabulary Segmentation

Yongkang Li, Tianheng Cheng, Bin Feng +2

Recent open-vocabulary segmentation methods adopt mask generators to predict segmentation masks and leverage pre-trained vision-language models, e.g., CLIP, to classify these masks…

cs.CV2024

ControlAR: Controllable Image Generation with Autoregressive Models

Zongming Li, Tianheng Cheng, Shoufa Chen +6

Autoregressive (AR) models have reformulated image generation as next-token prediction, demonstrating remarkable potential and emerging as strong competitors to diffusion models. H…

cs.CV2024★ 1 cited

Occupancy as Set of Points

Yiang Shi, Tianheng Cheng, Qian Zhang +2

In this paper, we explore a novel point representation for 3D occupancy prediction from multi-view images, which is named Occupancy as Set of Points. Existing camera-based methods…

cs.CV2024

EVF-SAM: Early Vision-Language Fusion for Text-Prompted Segment Anything Model

Yuxuan Zhang, Tianheng Cheng, Lianghui Zhu +7

Segment Anything Model (SAM) has attracted widespread attention for its superior interactive segmentation capabilities with visual prompts while lacking further exploration of text…

cs.CV2024★ 28 cited

YOLO-World: Real-Time Open-Vocabulary Object Detection

Tianheng Cheng, Lin Song, Yixiao Ge +3

The You Only Look Once (YOLO) series of detectors have established themselves as efficient and practical tools. However, their reliance on predefined and trained object categories…

cs.CV2023★ 14 cited

ProRes: Exploring Degradation-aware Visual Prompt for Universal Image Restoration

Jiaqi Ma, Tianheng Cheng, Guoli Wang +3

Image restoration aims to reconstruct degraded images, e.g., denoising or deblurring. Existing works focus on designing task-specific methods and there are inadequate attempts at u…

cs.CV2023★ 5 cited

Symphonize 3D Semantic Scene Completion with Contextual Instance Queries

Haoyi Jiang, Tianheng Cheng, Naiyu Gao +4

`3D Semantic Scene Completion (SSC) has emerged as a nascent and pivotal undertaking in autonomous driving, aiming to predict voxel occupancy within volumetric scenes. However, pre…

cs.CV2023★ 13 cited

TinyDet: Accurate Small Object Detection in Lightweight Generic Detectors

Shaoyu Chen, Tianheng Cheng, Jiemin Fang +4

Small object detection requires the detection head to scan a large number of positions on image feature maps, which is extremely hard for computation- and energy-efficient lightwei…

cs.CV2023★ 2 cited

VMA: Divide-and-Conquer Vectorized Map Annotation System for Large-Scale Driving Scene

Shaoyu Chen, Yunchi Zhang, Bencheng Liao +7

High-definition (HD) map serves as the essential infrastructure of autonomous driving. In this work, we build up a systematic vectorized map annotation framework (termed VMA) for e…

cs.CV2023

MobileInst: Video Instance Segmentation on the Mobile

Renhong Zhang, Tianheng Cheng, Shusheng Yang +8

Video instance segmentation on mobile devices is an important yet very challenging edge AI problem. It mainly suffers from (1) heavy computation and memory costs for frame-by-frame…

cs.CV2023★ 5 cited

Lane Graph as Path: Continuity-preserving Path-wise Modeling for Online Lane Graph Construction

Bencheng Liao, Shaoyu Chen, Bo Jiang +5

Online lane graph construction is a promising but challenging task in autonomous driving. Previous methods usually model the lane graph at the pixel or piece level, and recover the…

cs.CV2022★ 4 cited

Perceive, Interact, Predict: Learning Dynamic and Static Clues for End-to-End Motion Prediction

Bo Jiang, Shaoyu Chen, Xinggang Wang +7

Motion prediction is highly relevant to the perception of dynamic objects and static map elements in the scenarios of autonomous driving. In this work, we propose PIP, the first en…

cs.CV2022★ 4 cited

BoxTeacher: Exploring High-Quality Pseudo Labels for Weakly Supervised Instance Segmentation

Tianheng Cheng, Xinggang Wang, Shaoyu Chen +2

Labeling objects with pixel-wise segmentation requires a huge amount of human labor compared to bounding boxes. Most existing methods for weakly supervised instance segmentation fo…

cs.CV2022★ 69 cited

MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction

Bencheng Liao, Shaoyu Chen, Xinggang Wang +4

High-definition (HD) map provides abundant and precise environmental information of the driving scene, serving as a fundamental and indispensable component for planning in autonomo…

cs.CV2022★ 7 cited

Vision-based Uneven BEV Representation Learning with Polar Rasterization and Surface Estimation

Zhi Liu, Shaoyu Chen, Xiaojie Guo +6

In this work, we propose PolarBEV for vision-based uneven BEV representation learning. To adapt to the foreshortening effect of camera imaging, we rasterize the BEV space both angu…

cs.CV2022★ 17 cited

Polar Parametrization for Vision-based Surround-View 3D Detection

Shaoyu Chen, Xinggang Wang, Tianheng Cheng +3

3D detection based on surround-view camera system is a critical technique in autopilot. In this work, we present Polar Parametrization for 3D detection, which reformulates position…

cs.CV2022

Featurized Query R-CNN

Wenqiang Zhang, Tianheng Cheng, Xinggang Wang +3

The query mechanism introduced in the DETR method is changing the paradigm of object detection and recently there are many query-based methods have obtained strong object detection…

cs.CV2022★ 28 cited

Efficient and Robust 2D-to-BEV Representation Learning via Geometry-guided Kernel Transformer

Shaoyu Chen, Tianheng Cheng, Xinggang Wang +3

Learning Bird's Eye View (BEV) representation from surrounding-view cameras is of great importance for autonomous driving. In this work, we propose a Geometry-guided Kernel Transfo…

cs.CV2022★ 2 cited

Knowledge Mining with Scene Text for Fine-Grained Recognition

Hao Wang, Junchao Liao, Tianheng Cheng +5

Recently, the semantics of scene text has been proven to be essential in fine-grained image classification. However, the existing methods mainly exploit the literal meaning of scen…