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Models/CLIP-C

CLIP-C

Reported on 15 benchmarks across 1 task · 1 paper · 15 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision15 results

  • Text-based Person Retrieval with Noisy CorrespondenceonICFG-PEDES
    Rank 1· uses extra data· 2021-02-26
    55.25
    best: 66.54 (RDE)
    SOTA
    Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020
  • Text-based Person Retrieval with Noisy CorrespondenceonICFG-PEDES
    Rank-10· uses extra data· 2021-02-26
    81.32
    best: 86.7 (RDE)
    SOTA
    Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020
  • Text-based Person Retrieval with Noisy CorrespondenceonICFG-PEDES
    Rank-5· uses extra data· 2021-02-26
    74.76
    best: 81.7 (RDE)
    SOTA
    Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020
  • Text-based Person Retrieval with Noisy CorrespondenceonICFG-PEDES
    mAP· uses extra data· 2021-02-26
    31.09
    best: 39.08 (RDE)
    SOTA
    Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020
  • Text-based Person Retrieval with Noisy CorrespondenceonICFG-PEDES
    mINP· uses extra data· 2021-02-26
    4.94
    best: 8.77 (IVT)
    SOTA
    Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020
  • Text-based Person Retrieval with Noisy CorrespondenceonRSTPReid
    Rank 1· uses extra data· 2021-02-26
    54.45
    best: 64.45 (RDE)
    SOTA
    Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020
  • Text-based Person Retrieval with Noisy CorrespondenceonRSTPReid
    Rank 10· uses extra data· 2021-02-26
    86.7
    best: 90 (RDE)
    SOTA
    Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020
  • Text-based Person Retrieval with Noisy CorrespondenceonRSTPReid
    Rank 5· uses extra data· 2021-02-26
    77.8
    best: 83.5 (RDE)
    SOTA
    Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020
  • Text-based Person Retrieval with Noisy CorrespondenceonRSTPReid
    mAP· uses extra data· 2021-02-26
    42.58
    best: 49.78 (RDE)
    SOTA
    Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020
  • Text-based Person Retrieval with Noisy CorrespondenceonRSTPReid
    mINP· uses extra data· 2021-02-26
    21.38
    best: 27.43 (RDE)
    SOTA
    Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020
  • Text-based Person Retrieval with Noisy CorrespondenceonCUHK-PEDES
    Rank 10· uses extra data· 2021-02-26
    90.89
    best: 93.63 (RDE)
    SOTA
    Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020
  • Text-based Person Retrieval with Noisy CorrespondenceonCUHK-PEDES
    Rank-1· uses extra data· 2021-02-26
    66.41
    best: 74.46 (RDE)
    SOTA
    Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020
  • Text-based Person Retrieval with Noisy CorrespondenceonCUHK-PEDES
    Rank-5· uses extra data· 2021-02-26
    85.15
    best: 89.42 (RDE)
    SOTA
    Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020
  • Text-based Person Retrieval with Noisy CorrespondenceonCUHK-PEDES
    mAP· uses extra data· 2021-02-26
    59.36
    best: 66.13 (RDE)
    SOTA
    Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020
  • Text-based Person Retrieval with Noisy CorrespondenceonCUHK-PEDES
    mINP· uses extra data· 2021-02-26
    43.02
    best: 49.66 (RDE)
    SOTA
    Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020