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신 정민

About Posts
[CVPR2022] SimMIM: a Simple Framework for Masked Image Modeling
  • Posted on: 03/12/2023 –
  • Comments: 8 Comments
[AAAI2023](Oral) Compact Transformer Tracker with Correlative Masked Modeling
  • Posted on: 03/04/2023 –
  • Comments: No Comments
[CVPR2022] Masked Feature Prediction for Self-Supervised Visual Pre-Training
  • Posted on: 02/12/2023 –
  • Comments: 4 Comments
문체부과제 제안서 작성 관련
  • Posted on: 02/05/2023 –
  • Comments: 1 Comment
[Arxiv2022] Masked Autoencoders are Robust Data Augmentors
  • Posted on: 01/29/2023 –
  • Comments: 2 Comments
[NeurIPS2022] Croco: Self-supervised Pre-training for 3D Vision tasks by Cross-view Completion
  • Posted on: 01/15/2023 –
  • Comments: 2 Comments
[ECCV2022]MultiMAE: Multi-modal Multi-task Masked Autoencoders
  • Posted on: 01/06/2023 –
  • Comments: No Comments
Self-supervised Learning
  • Posted on: 12/15/2022 –
  • Comments: No Comments
[ICLR2019] ImageNet-Trained CNNs are Biased Towards Texture; Increasing Shape Bias Improves Accuracy And Robustness
  • Posted on: 12/09/2022 –
  • Comments: 3 Comments
[CVPR2022] Toward Practical Monocular Indoor Depth Estimation
  • Posted on: 12/03/2022 –
  • Comments: 4 Comments
Newer Posts 1 2 … 5 6 7 … 15 16 Older Posts

Conference Deadline

NEW POST

  • [arXiv 2025] VideoRAG: Retrieval-Augmented Generation over Video Corpus
  • [WACV 2026] UNO: Unifying One-stage Video Scene Graph Generation via Object-Centric Visual Representation Learning
  • DexMimicGen: Automated Data Generation for Bimanual Dexterous Manipulation via Imitation Learning
  • [NeurIPS 2020]Object-Centric Learning with Slot Attention
  • [ICRA 2024]NoMaD : Goal Masked Diffusion Policies for Navigation and Exploration

New Comment

  1. 김 영규 on [NeurIPS 2025] PhysX-3D: Physical-Grounded 3D Asset Generation11/26/2025

    안녕하세요 정민님 댓글 감사합니다. 정리를 하자면 Absolute Scale의 경우는 사람이 직접 기입합니다. Kinematics에 관련된 부분도 수학적인 기하 알고리즘을 통해 접촉면…

  2. 김 영규 on [NeurIPS 2025] PhysX-3D: Physical-Grounded 3D Asset Generation11/26/2025

    안녕하세요 우현님, 다른 리뷰에 대한 댓글인것 같긴 한데, 일단 답변 드리겠습니다 우선 Robo-SAM 자체가 segment 해야하는게 쉽게 로봇, task 관련…

  3. 김 영규 on [IROS 2025] RoboEngine: Plug-and-Play Robot Data Augmentation with Semantic Robot Segmentation and Background Generation11/26/2025

    안녕하세요 정우님 댓글 감사합니다. 답변이 늦어 죄송합니다 음.. 일단 최근 Imitation Learning 모델들은 rollout 단위로 학습하지 않고 video 기준으로 특정…

  4. 김 영규 on [IROS 2025] RoboEngine: Plug-and-Play Robot Data Augmentation with Semantic Robot Segmentation and Background Generation11/26/2025

    안녕하세요 정민님 댓글 감사합니다. 답변이 늦은점 죄송합니다,, A 1,2 (제가 설명을 깔끔하게 못 한것 같습니다,,) Robo-SAM이 저자들이 제안한 3800장의 데이터셋으로…

  5. 신 인택 on [NeurIPS 2020]Object-Centric Learning with Slot Attention11/25/2025

    안녕하세요 재연님 답글 감사합니다. 각 질문에 대해서 답글을 달아드리자면 1. 논문에서 learnable slot 에 대해서 언급하지는 않았으나 random sampled slot이…

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