214 citations · 999 across the 56 of their papers we have counts for
9 papers · 2 filters
Global Context Networks
Yue Cao, Jiarui Xu, Stephen Lin +2
The Non-Local Network (NLNet) presents a pioneering approach for capturing long-range dependencies within an image, via aggregating query-specific global context to each query posi…
Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning
Zhenda Xie, Yutong Lin, Zheng Zhang +3
Contrastive learning methods for unsupervised visual representation learning have reached remarkable levels of transfer performance. We argue that the power of contrastive learning…
RelationNet++: Bridging Visual Representations for Object Detection via Transformer Decoder
Cheng Chi, Fangyun Wei, Han Hu
Existing object detection frameworks are usually built on a single format of object/part representation, i.e., anchor/proposal rectangle boxes in RetinaNet and Faster R-CNN, center…
RepPoints V2: Verification Meets Regression for Object Detection
Yihong Chen, Zheng Zhang, Yue Cao +3
Verification and regression are two general methodologies for prediction in neural networks. Each has its own strengths: verification can be easier to infer accurately, and regress…
A Closer Look at Local Aggregation Operators in Point Cloud Analysis
Ze Liu, Han Hu, Yue Cao +2
Recent advances of network architecture for point cloud processing are mainly driven by new designs of local aggregation operators. However, the impact of these operators to networ…
Parametric Instance Classification for Unsupervised Visual Feature Learning
Yue Cao, Zhenda Xie, Bin Liu +3
This paper presents parametric instance classification (PIC) for unsupervised visual feature learning. Unlike the state-of-the-art approaches which do instance discrimination in a…