5 citations · 14 across the 4 of their papers we have counts for
9 papers · 1 filter
SEGIC: Unleashing the Emergent Correspondence for In-Context Segmentation
Lingchen Meng, Shiyi Lan, Hengduo Li +3
In-context segmentation aims at segmenting novel images using a few labeled example images, termed as "in-context examples", exploring content similarities between examples and the…
FocalFormer3D : Focusing on Hard Instance for 3D Object Detection
Yilun Chen, Zhiding Yu, Yukang Chen +4
False negatives (FN) in 3D object detection, {\em e.g.}, missing predictions of pedestrians, vehicles, or other obstacles, can lead to potentially dangerous situations in autonomou…
FB-OCC: 3D Occupancy Prediction based on Forward-Backward View Transformation
Zhiqi Li, Zhiding Yu, David Austin +4
This technical report summarizes the winning solution for the 3D Occupancy Prediction Challenge, which is held in conjunction with the CVPR 2023 Workshop on End-to-End Autonomous D…
1st Place Solution of The Robust Vision Challenge 2022 Semantic Segmentation Track
Junfei Xiao, Zhichao Xu, Shiyi Lan +3
This report describes the winning solution to the Robust Vision Challenge (RVC) semantic segmentation track at ECCV 2022. Our method adopts the FAN-B-Hybrid model as the encoder an…
DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision
Shiyi Lan, Zhiding Yu, Christopher Choy +5
We introduce DiscoBox, a novel framework that jointly learns instance segmentation and semantic correspondence using bounding box supervision. Specifically, we propose a self-ensem…
M3DeTR: Multi-representation, Multi-scale, Mutual-relation 3D Object Detection with Transformers
Tianrui Guan, Jun Wang, Shiyi Lan +4
We present a novel architecture for 3D object detection, M3DeTR, which combines different point cloud representations (raw, voxels, bird-eye view) with different feature scales bas…