Camera-Incremental Object Re-Identification with Identity Knowledge Evolution

• URL: http://arxiv.org/abs/2305.15909v1
• Date: Thu, 25 May 2023 10:15:29 GMT
• Title: Camera-Incremental Object Re-Identification with Identity Knowledge Evolution
• Authors: Hantao Yao, Lu Yu, Jifei Luo, Changsheng Xu
• Abstract summary: Object Re-identification (ReID) aims to retrieve the probe object from many gallery images by associating and collecting the identities across all camera views. When deploying the ReID algorithm in real-world scenarios, the aspect of storage, privacy constraints, and dynamic changes of cameras would degrade its generalizability and applicability. Treating each camera's data independently, we introduce a novel ReID task named Camera-Incremental Object Re-identification (CIOR) by continually optimizing the ReID mode from the incoming stream of the camera dataset.
• Score: 82.64836424135886
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Object Re-identification (ReID) aims to retrieve the probe object from many gallery images with the ReID model inferred based on a stationary camera-free dataset by associating and collecting the identities across all camera views. When deploying the ReID algorithm in real-world scenarios, the aspect of storage, privacy constraints, and dynamic changes of cameras would degrade its generalizability and applicability. Treating each camera's data independently, we introduce a novel ReID task named Camera-Incremental Object Re-identification (CIOR) by continually optimizing the ReID mode from the incoming stream of the camera dataset. Since the identities under different camera views might describe the same object, associating and distilling the knowledge of common identities would boost the discrimination and benefit from alleviating the catastrophic forgetting. In this paper, we propose a novel Identity Knowledge Evolution (IKE) framework for CIOR, consisting of the Identity Knowledge Association (IKA), Identity Knowledge Distillation (IKD), and Identity Knowledge Update (IKU). IKA is proposed to discover the common identities between the current identity and historical identities. IKD has applied to distillate historical identity knowledge from common identities and quickly adapt the historical model to the current camera view. After each camera has been trained, IKU is applied to continually expand the identity knowledge by combining the historical and current identity memories. The evaluation of Market-CL and Veri-CL shows the Identity Knowledge Evolution (IKE) effectiveness for CIOR. code:https://github.com/htyao89/Camera-Incremental-Object-ReID

Related papers

• AnyMaker: Zero-shot General Object Customization via Decoupled Dual-Level ID Injection [72.41427550339296]
  We introduce AnyMaker, a framework capable of generating general objects with high ID fidelity and flexible text editability. The efficacy of AnyMaker stems from its novel general ID extraction, dual-level ID injection, and ID-aware decoupling. To validate our approach and boost the research of general object customization, we create the first large-scale general ID dataset.
  arXiv  Detail & Related papers  (2024-06-17T15:26:22Z)
• ID-Aligner: Enhancing Identity-Preserving Text-to-Image Generation with Reward Feedback Learning [57.91881829308395]
  Identity-preserving text-to-image generation (ID-T2I) has received significant attention due to its wide range of application scenarios like AI portrait and advertising. We present textbfID-Aligner, a general feedback learning framework to enhance ID-T2I performance.
  arXiv  Detail & Related papers  (2024-04-23T18:41:56Z)
• X-ReID: Cross-Instance Transformer for Identity-Level Person Re-Identification [53.047542904329866]
  Cross Intra-Identity Instances module (IntraX) fuses different intra-identity instances to transfer Identity-Level knowledge. Cross Inter-Identity Instances module (InterX) involves hard positive and hard negative instances to improve the attention response to the same identity.
  arXiv  Detail & Related papers  (2023-02-04T03:16:18Z)
• Handling Label Uncertainty for Camera Incremental Person Re-Identification [17.5026399908583]
  Incremental learning for person re-identification (ReID) aims to develop models that can be trained with a continuous data stream. New data collected from new cameras may probably contain an unknown proportion of identities seen before. We propose a novel framework ExtendOVA to handle the class overlap issue.
  arXiv  Detail & Related papers  (2022-10-17T02:59:54Z)
• Towards Privacy-Preserving Person Re-identification via Person Identify Shift [19.212691296927165]
  Person re-identification (ReID) requires preserving the privacy of pedestrian images used by ReID methods. We propose a novel de-identification method designed explicitly for person ReID, named Person Identify Shift (PIS) PIS shifts each pedestrian image from the current identity to another with a new identity, resulting in images still preserving the relative identities.
  arXiv  Detail & Related papers  (2022-07-15T06:58:41Z)
• Seq-Masks: Bridging the gap between appearance and gait modeling for video-based person re-identification [10.490428828061292]
  ideo-based person re-identification (Re-ID) aims to match person images in video sequences captured by disjoint surveillance cameras. Traditional video-based person Re-ID methods focus on exploring appearance information, thus, vulnerable against illumination changes, scene noises, camera parameters, and especially clothes/carrying variations. We propose a framework that utilizes the sequence masks (SeqMasks) in the video to integrate appearance information and gait modeling in a close fashion.
  arXiv  Detail & Related papers  (2021-12-10T16:00:20Z)
• Intra-Camera Supervised Person Re-Identification [87.88852321309433]
  We propose a novel person re-identification paradigm based on an idea of independent per-camera identity annotation. This eliminates the most time-consuming and tedious inter-camera identity labelling process. We formulate a Multi-tAsk mulTi-labEl (MATE) deep learning method for Intra-Camera Supervised (ICS) person re-id.
  arXiv  Detail & Related papers  (2020-02-12T15:26:33Z)
• Towards Precise Intra-camera Supervised Person Re-identification [54.86892428155225]
  Intra-camera supervision (ICS) for person re-identification (Re-ID) assumes that identity labels are independently annotated within each camera view. Lack of inter-camera labels makes the ICS Re-ID problem much more challenging than the fully supervised counterpart. Our approach performs even comparable to state-of-the-art fully supervised methods in two of the datasets.
  arXiv  Detail & Related papers  (2020-02-12T11:56:30Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.