2.4k citations · 2.9k across the 18 of their papers we have counts for
8 papers · 1 filter
FB-BEV: BEV Representation from Forward-Backward View Transformations
Zhiqi Li, Zhiding Yu, Wenhai Wang +3
View Transformation Module (VTM), where transformations happen between multi-view image features and Bird-Eye-View (BEV) representation, is a crucial step in camera-based BEV perce…
The All-Seeing Project: Towards Panoptic Visual Recognition and Understanding of the Open World
Weiyun Wang, Min Shi, Qingyun Li +11
We present the All-Seeing (AS) project: a large-scale data and model for recognizing and understanding everything in the open world. Using a scalable data engine that incorporates…
AVSegFormer: Audio-Visual Segmentation with Transformer
Shengyi Gao, Zhe Chen, Guo Chen +2
The combination of audio and vision has long been a topic of interest in the multi-modal community. Recently, a new audio-visual segmentation (AVS) task has been introduced, aiming…
VisionLLM: Large Language Model is also an Open-Ended Decoder for Vision-Centric Tasks
Wenhai Wang, Zhe Chen, Xiaokang Chen +8
Large language models (LLMs) have notably accelerated progress towards artificial general intelligence (AGI), with their impressive zero-shot capacity for user-tailored tasks, endo…
GridFormer: Residual Dense Transformer with Grid Structure for Image Restoration in Adverse Weather Conditions
Tao Wang, Kaihao Zhang, Ziqian Shao +6
Image restoration in adverse weather conditions is a difficult task in computer vision. In this paper, we propose a novel transformer-based framework called GridFormer which serves…
Graph Propagation Transformer for Graph Representation Learning
Zhe Chen, Hao Tan, Tao Wang +5
This paper presents a novel transformer architecture for graph representation learning. The core insight of our method is to fully consider the information propagation among nodes…
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…
Champion Solution for the WSDM2023 Toloka VQA Challenge
Shengyi Gao, Zhe Chen, Guo Chen +2
In this report, we present our champion solution to the WSDM2023 Toloka Visual Question Answering (VQA) Challenge. Different from the common VQA and visual grounding (VG) tasks, th…