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Found 11 papers, 7 papers with code
STC: Spatio-Temporal Contrastive Learning for Video Instance Segmentation
Video Instance Segmentation (VIS) is a task that simultaneously requires classification, segmentation, and instance association in a video.
Ranked #2 on
Video Instance Segmentation
on OVIS validation
Rethinking Counting and Localization in Crowds:A Purely Point-Based Framework
In this paper, we propose a purely point-based framework for joint crowd counting and individual localization.
SiamRCR: Reciprocal Classification and Regression for Visual Object Tracking
In addition, we add a localization branch to predict the localization accuracy, so that it can work as the replacement of the regression assistance link during inference.
Rethinking Counting and Localization in Crowds: A Purely Point-Based Framework
In this paper, we propose a purely point-based framework for joint crowd counting and individual localization.
Fine-Grained Dynamic Head for Object Detection
To this end, we propose a fine-grained dynamic head to conditionally select a pixel-level combination of FPN features from different scales for each instance, which further releases the ability of multi-scale feature representation.
Rethinking Learnable Tree Filter for Generic Feature Transform
The Learnable Tree Filter presents a remarkable approach to model structure-preserving relations for semantic segmentation.
Contrastive Visual-Linguistic Pretraining
We evaluate CVLP on several down-stream tasks, including VQA, GQA and NLVR2 to validate the superiority of contrastive learning on multi-modality representation learning.
AutoAssign: Differentiable Label Assignment for Dense Object Detection
During training, to both satisfy the prior distribution of data and adapt to category characteristics, we present Center Weighting to adjust the category-specific prior distributions.
Learning Where to Focus for Efficient Video Object Detection
Transferring existing image-based detectors to the video is non-trivial since the quality of frames is always deteriorated by part occlusion, rare pose, and motion blur.
Ranked #10 on
Video Object Detection
on ImageNet VID
Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection
This report presents our method which wins the nuScenes3D Detection Challenge [17] held in Workshop on Autonomous Driving(WAD, CVPR 2019).
Ranked #176 on
3D Object Detection
on nuScenes
Dynamic Fusion with Intra- and Inter- Modality Attention Flow for Visual Question Answering
It can robustly capture the high-level interactions between language and vision domains, thus significantly improves the performance of visual question answering.
