226 citations · 1.6k across the 138 of their papers we have counts for
15 papers · 2 filters
Benchmarking Robustness of Multimodal Image-Text Models under Distribution Shift
Jielin Qiu, Yi Zhu, Xingjian Shi +5
Multimodal image-text models have shown remarkable performance in the past few years. However, evaluating robustness against distribution shifts is crucial before adopting them in…
CU-Net: LiDAR Depth-Only Completion With Coupled U-Net
Yufei Wang, Yuchao Dai, Qi Liu +3
LiDAR depth-only completion is a challenging task to estimate dense depth maps only from sparse measurement points obtained by LiDAR. Even though the depth-only methods have been w…
Improving Long-tailed Object Detection with Image-Level Supervision by Multi-Task Collaborative Learning
Bo Li, Yongqiang Yao, Jingru Tan +4
Data in real-world object detection often exhibits the long-tailed distribution. Existing solutions tackle this problem by mitigating the competition between the head and tail cate…
The Equalization Losses: Gradient-Driven Training for Long-tailed Object Recognition
Jingru Tan, Bo Li, Xin Lu +4
Long-tail distribution is widely spread in real-world applications. Due to the extremely small ratio of instances, tail categories often show inferior accuracy. In this paper, we f…
Semantics-Consistent Cross-domain Summarization via Optimal Transport Alignment
Jielin Qiu, Jiacheng Zhu, Mengdi Xu +6
Multimedia summarization with multimodal output (MSMO) is a recently explored application in language grounding. It plays an essential role in real-world applications, i.e., automa…
Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021
Carole H. Sudre, Kimberlin Van Wijnen, Florian Dubost +46
Imaging markers of cerebral small vessel disease provide valuable information on brain health, but their manual assessment is time-consuming and hampered by substantial intra- and…
Light-YOLOv5: A Lightweight Algorithm for Improved YOLOv5 in Complex Fire Scenarios
Hao Xu, Bo Li, Fei Zhong
Fire-detection technology is of great importance for successful fire-prevention measures. Image-based fire detection is one effective method. At present, object-detection algorithm…
Target-Relevant Knowledge Preservation for Multi-Source Domain Adaptive Object Detection
Jiaxi Wu, Jiaxin Chen, Mengzhe He +7
Domain adaptive object detection (DAOD) is a promising way to alleviate performance drop of detectors in new scenes. Albeit great effort made in single source domain adaptation, a…
MHMS: Multimodal Hierarchical Multimedia Summarization
Jielin Qiu, Jiacheng Zhu, Mengdi Xu +6
Multimedia summarization with multimodal output can play an essential role in real-world applications, i.e., automatically generating cover images and titles for news articles or p…
Unsupervised Learning of Accurate Siamese Tracking
Qiuhong Shen, Lei Qiao, Jinyang Guo +7
Unsupervised learning has been popular in various computer vision tasks, including visual object tracking. However, prior unsupervised tracking approaches rely heavily on spatial s…
Towards Practical Certifiable Patch Defense with Vision Transformer
Zhaoyu Chen, Bo Li, Jianghe Xu +3
Patch attacks, one of the most threatening forms of physical attack in adversarial examples, can lead networks to induce misclassification by modifying pixels arbitrarily in a cont…
Domain Generalization using Pretrained Models without Fine-tuning
Ziyue Li, Kan Ren, Xinyang Jiang +3
Fine-tuning pretrained models is a common practice in domain generalization (DG) tasks. However, fine-tuning is usually computationally expensive due to the ever-growing size of pr…
Backbone is All Your Need: A Simplified Architecture for Visual Object Tracking
Boyu Chen, Peixia Li, Lei Bai +6
Exploiting a general-purpose neural architecture to replace hand-wired designs or inductive biases has recently drawn extensive interest. However, existing tracking approaches rely…
TPC: Transformation-Specific Smoothing for Point Cloud Models
Wenda Chu, Linyi Li, Bo Li
Point cloud models with neural network architectures have achieved great success and have been widely used in safety-critical applications, such as Lidar-based recognition systems…
Equalized Focal Loss for Dense Long-Tailed Object Detection
Bo Li, Yongqiang Yao, Jingru Tan +4
Despite the recent success of long-tailed object detection, almost all long-tailed object detectors are developed based on the two-stage paradigm. In practice, one-stage detectors…