Dollár, Piotr

Microsoft COCO: Common Objects in Context

Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., & Zitnick, C. L. (2014) · Lecture Notes in Computer Science

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 45,460

Segment Anything

Kirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A. C., Lo, W.-Y., et al. (2023) · 2023 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 11,953

Edge Boxes: Locating Object Proposals from Edges

Zitnick, C. L., & Dollár, P. (2014) · Lecture Notes in Computer Science

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 2,656

Microsoft COCO: Common Objects in Context

Lin, T.-Y., Maire, M., Belongie, S., Bourdev, L., Girshick, R., Hays, J., Perona, P., Ramanan, D., Zitnick, C. L., & Dollár, P. (2014) · arXiv

Human Pose and Action RecognitionAdvanced Neural Network Applications

Cited by 2,579

Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Goyal, P., Dollár, P., Girshick, R., Noordhuis, P., Wesolowski, L., Kyrola, A., Tulloch, A., Jia, Y., & He, K. (2017) · arXiv

Stochastic Gradient Optimization TechniquesParallel Computing and Optimization Techniques

Cited by 2,294

Panoptic Segmentation

Kirillov, A., He, K., Girshick, R., Rother, C., & Dollár, P. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 1,659

Panoptic Feature Pyramid Networks

Kirillov, A., Girshick, R., He, K., & Dollár, P. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 1,460

Focal Loss for Dense Object Detection

Lin, T.-Y., Goyal, P., Girshick, R., He, K., & Dollár, P. (2017) · arXiv

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 1,227

Segment Anything

Kirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A. C., Lo, W.-Y., et al. (2023) · arXiv

Advanced Neural Network ApplicationsIndustrial Vision Systems and Defect Detection

Cited by 527

Mask R-CNN

He, K., Gkioxari, G., Dollár, P., & Girshick, R. (2017) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 406

SAM 2: Segment Anything in Images and Videos

Ravi, N., Gabeur, V., Hu, Y.-T., Hu, R., Ryali, C., Ma, T., Khedr, H., Rädle, R., Rolland, C., Gustafson, L., et al. (2024) · arXiv

Advanced Neural Network ApplicationsMultimodal Machine Learning Applications

Cited by 300

Perception Encoder: The best visual embeddings are not at the output of the network

Bolya, D., Huang, P.-Y., Sun, P., Cho, J. H., Madotto, A., Wei, C., Ma, T., Zhi, J., Rajasegaran, J., Rasheed, H., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 19

PerceptionLM: Open-Access Data and Models for Detailed Visual Understanding

Cho, J. H., Madotto, A., Mavroudi, E., Afouras, T., Nagarajan, T., Maaz, M., Song, Y., Ma, T., Hu, S., Jain, S., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsHuman Pose and Action Recognition

Cited by 8