2.4k citations · 3.4k across the 57 of their papers we have counts for
59 papers
RestoreFormer++: Towards Real-World Blind Face Restoration from Undegraded Key-Value Pairs
Zhouxia Wang, Jiawei Zhang, Tianshui Chen +2
Blind face restoration aims at recovering high-quality face images from those with unknown degradations. Current algorithms mainly introduce priors to complement high-quality detai…
MetaBEV: Solving Sensor Failures for BEV Detection and Map Segmentation
Chongjian Ge, Junsong Chen, Enze Xie +5
Perception systems in modern autonomous driving vehicles typically take inputs from complementary multi-modal sensors, e.g., LiDAR and cameras. However, in real-world applications,…
DeepAccident: A Motion and Accident Prediction Benchmark for V2X Autonomous Driving
Tianqi Wang, Sukmin Kim, Wenxuan Ji +5
Safety is the primary priority of autonomous driving. Nevertheless, no published dataset currently supports the direct and explainable safety evaluation for autonomous driving. In…
Vehicle-Infrastructure Cooperative 3D Object Detection via Feature Flow Prediction
Haibao Yu, Yingjuan Tang, Enze Xie +4
Cooperatively utilizing both ego-vehicle and infrastructure sensor data can significantly enhance autonomous driving perception abilities. However, temporal asynchrony and limited…
DDP: Diffusion Model for Dense Visual Prediction
Yuanfeng Ji, Zhe Chen, Enze Xie +6
We propose a simple, efficient, yet powerful framework for dense visual predictions based on the conditional diffusion pipeline. Our approach follows a "noise-to-map" generative pa…
Dense Distinct Query for End-to-End Object Detection
Shilong Zhang, Xinjiang Wang, Jiaqi Wang +5
One-to-one label assignment in object detection has successfully obviated the need for non-maximum suppression (NMS) as postprocessing and makes the pipeline end-to-end. However, i…
Fast-BEV: Towards Real-time On-vehicle Bird's-Eye View Perception
Bin Huang, Yangguang Li, Enze Xie +7
Recently, the pure camera-based Bird's-Eye-View (BEV) perception removes expensive Lidar sensors, making it a feasible solution for economical autonomous driving. However, most exi…
DiffusionDet: Diffusion Model for Object Detection
Shoufa Chen, Peize Sun, Yibing Song +1
We propose DiffusionDet, a new framework that formulates object detection as a denoising diffusion process from noisy boxes to object boxes. During the training stage, object boxes…
Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipe
Hongyang Li, Chonghao Sima, Jifeng Dai +19
Learning powerful representations in bird's-eye-view (BEV) for perception tasks is trending and drawing extensive attention both from industry and academia. Conventional approaches…
PoseTrans: A Simple Yet Effective Pose Transformation Augmentation for Human Pose Estimation
Wentao Jiang, Sheng Jin, Wentao Liu +3
Human pose estimation aims to accurately estimate a wide variety of human poses. However, existing datasets often follow a long-tailed distribution that unusual poses only occupy a…
Towards Grand Unification of Object Tracking
Bin Yan, Yi Jiang, Peize Sun +4
We present a unified method, termed Unicorn, that can simultaneously solve four tracking problems (SOT, MOT, VOS, MOTS) with a single network using the same model parameters. Due t…
3D Interacting Hand Pose Estimation by Hand De-occlusion and Removal
Hao Meng, Sheng Jin, Wentao Liu +4
Estimating 3D interacting hand pose from a single RGB image is essential for understanding human actions. Unlike most previous works that directly predict the 3D poses of two inter…
CO^3: Cooperative Unsupervised 3D Representation Learning for Autonomous Driving
Runjian Chen, Yao Mu, Runsen Xu +5
Unsupervised contrastive learning for indoor-scene point clouds has achieved great successes. However, unsupervised learning point clouds in outdoor scenes remains challenging beca…
MBEV: Multi-Camera Joint 3D Detection and Segmentation with Unified Birds-Eye View Representation
Enze Xie, Zhiding Yu, Daquan Zhou +5
In this paper, we propose MBEV, a unified framework that jointly performs 3D object detection and map segmentation in the Birds Eye View~(BEV) space with multi-camera image inp…
DaViT: Dual Attention Vision Transformers
Mingyu Ding, Bin Xiao, Noel Codella +3
In this work, we introduce Dual Attention Vision Transformers (DaViT), a simple yet effective vision transformer architecture that is able to capture global context while maintaini…
Scale-Equivalent Distillation for Semi-Supervised Object Detection
Qiushan Guo, Yao Mu, Jianyu Chen +3
Recent Semi-Supervised Object Detection (SS-OD) methods are mainly based on self-training, i.e., generating hard pseudo-labels by a teacher model on unlabeled data as supervisory s…
WegFormer: Transformers for Weakly Supervised Semantic Segmentation
Chunmeng Liu, Enze Xie, Wenjia Wang +3
Although convolutional neural networks (CNNs) have achieved remarkable progress in weakly supervised semantic segmentation (WSSS), the effective receptive field of CNN is insuffici…
Pseudo-Labeled Auto-Curriculum Learning for Semi-Supervised Keypoint Localization
Can Wang, Sheng Jin, Yingda Guan +4
Localizing keypoints of an object is a basic visual problem. However, supervised learning of a keypoint localization network often requires a large amount of data, which is expensi…
RestoreFormer: High-Quality Blind Face Restoration from Undegraded Key-Value Pairs
Zhouxia Wang, Jiawei Zhang, Runjian Chen +2
Blind face restoration is to recover a high-quality face image from unknown degradations. As face image contains abundant contextual information, we propose a method, RestoreFormer…
MetaCloth: Learning Unseen Tasks of Dense Fashion Landmark Detection from a Few Samples
Yuying Ge, Ruimao Zhang, Ping Luo
Recent advanced methods for fashion landmark detection are mainly driven by training convolutional neural networks on large-scale fashion datasets, which has a large number of anno…
Dynamic Token Normalization Improves Vision Transformers
Wenqi Shao, Yixiao Ge, Zhaoyang Zhang +4
Vision Transformer (ViT) and its variants (e.g., Swin, PVT) have achieved great success in various computer vision tasks, owing to their capability to learn long-range contextual i…
DanceTrack: Multi-Object Tracking in Uniform Appearance and Diverse Motion
Peize Sun, Jinkun Cao, Yi Jiang +4
A typical pipeline for multi-object tracking (MOT) is to use a detector for object localization, and following re-identification (re-ID) for object association. This pipeline is pa…
FAST: Faster Arbitrarily-Shaped Text Detector with Minimalist Kernel Representation
Zhe Chen, Jiahao Wang, Wenhai Wang +4
We propose an accurate and efficient scene text detection framework, termed FAST (i.e., faster arbitrarily-shaped text detector). Different from recent advanced text detectors that…
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers
Zhiqi Li, Wenhai Wang, Enze Xie +5
Panoptic segmentation involves a combination of joint semantic segmentation and instance segmentation, where image contents are divided into two types: things and stuff. We present…