665 citations · 3.1k across the 159 of their papers we have counts for
18 papers · 1 filter
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…
EVA: Exploring the Limits of Masked Visual Representation Learning at Scale
Yuxin Fang, Wen Wang, Binhui Xie +6
We launch EVA, a vision-centric foundation model to explore the limits of visual representation at scale using only publicly accessible data. EVA is a vanilla ViT pre-trained to re…
PD-Quant: Post-Training Quantization based on Prediction Difference Metric
Jiawei Liu, Lin Niu, Zhihang Yuan +3
Post-training quantization (PTQ) is a neural network compression technique that converts a full-precision model into a quantized model using lower-precision data types. Although it…
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…
Robust Multi-Object Tracking by Marginal Inference
Yifu Zhang, Chunyu Wang, Xinggang Wang +2
Multi-object tracking in videos requires to solve a fundamental problem of one-to-one assignment between objects in adjacent frames. Most methods address the problem by first disca…
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…