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Related Concept Videos

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Memory is categorized into three major systems: sensory memory, short-term memory (STM), and long-term memory (LTM). These systems differ in their capacity and the duration for which they can hold information. Sensory memory captures raw sensory input from the environment, holding it for just a few seconds or less. For example, on hearing a brief, loud sound, like a car horn honking, the sound seems to linger in the mind for a moment even after it stops. This is an instance of sensory memory...
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Improving short-term memory can be achieved through techniques like chunking and rehearsal. Chunking involves organizing information into larger, more manageable units. This technique is particularly useful for information that exceeds the typical memory span of between five and nine items. For instance, logging into an online account with a password like "ta89vq0179gz" involves grouping letters and numbers into three chunks—ta89, vq01, and 79gz. It makes large amounts of...
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Storage01:23

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A schema is a mental framework that helps individuals organize and interpret information. Schemata, formed from previous experiences, influence how we process new information: how we encode it, the inferences we make, and how we retrieve it. For instance, a schema for what a typical classroom looks like might include desks, a teacher's desk, a whiteboard, and students in such an environment. This expectation helps us quickly understand and navigate new classrooms without needing to analyze...
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Understanding Memory01:19

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Memory is the retention of information or experiences over time, facilitated through three main processes: encoding, storage, and retrieval. Encoding is the process of inputting information into the memory system. For instance, when listening to a lecture, watching a play, reading a book, or having a conversation, the brain is actively encoding information. This initial stage involves transforming sensory input into a form that can be processed and stored by the brain. Various factors, such as...
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Role of Hippocampus in Memory01:19

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The hippocampus, a critical brain structure, plays an essential role in memory processing, particularly in the formation and retrieval of memory. This small, seahorse-shaped region is located within the medial temporal lobe, with one hippocampus in each brain hemisphere. Experimental studies involving lesions in the hippocampi of rats have demonstrated significant impairments in tasks such as object recognition and maze navigation, indicating the hippocampus involvement in both recognition and...
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  3. Research Domains
  5. Information And Computing Sciences
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  9. Video Processing
  11. Memory Transmission Based Referring Video Object Segmentation.
  1. Home
  3. Research Domains
  5. Information And Computing Sciences
  7. Computer Vision And Multimedia Computation
  9. Video Processing
  11. Memory Transmission Based Referring Video Object Segmentation.

Related Experiment Video

Eye Movement Monitoring of Memory
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Eye Movement Monitoring of Memory

Published on: August 15, 2010

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Memory Transmission Based Referring Video Object Segmentation.

Zijin Liu1, Lichun Wang1, Yongli Hu1

  • 1Beijing Key Laboratory of Multimedia and Intelligent Software Technology Beijing Institute of Artificial Intelligence, China; School of Information Science and Technology Beijing University of Technology, Beijing, 100124, China.

Neural Networks : the Official Journal of the International Neural Network Society
|May 21, 2025

View abstract on PubMed

Summary
This summary is machine-generated.

This study introduces Memory Transmission Based Referring Video Object Segmentation (MT-RVOS) for improved video object segmentation. MT-RVOS enhances consistency by using previous frame masks to guide current frame segmentation, overcoming clip-level limitations.

Keywords:
Inter-frame modelingMemory transmissionReferring Video Object SegmentationText-Vision Interaction

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Area of Science:

  • Computer Vision
  • Artificial Intelligence

Background:

  • Referring Video Object Segmentation (RVOS) aims to segment objects in videos based on textual descriptions.
  • Current methods use clip-level inter-frame modeling for object consistency, but struggle with continuous motion across longer durations.

Purpose of the Study:

  • To propose a novel memory transmission-based continuous inter-frame modeling approach for RVOS.
  • To enhance the consistency of object segmentation throughout video sequences.

Main Methods:

  • Developed a memory transmission mechanism to propagate segmentation information between consecutive frames.
  • Introduced a pseudo mask generation from the previous frame's segmentation result.
  • Proposed the Memory Transmission Based Referring Video Object Segmentation (MT-RVOS) model that utilizes this pseudo mask for guiding current frame segmentation.

Main Results:

  • MT-RVOS demonstrated competitive performance on four benchmark datasets.
  • The proposed method effectively addresses the limitations of clip-level modeling in capturing continuous object motion.

Conclusions:

  • Memory transmission-based continuous inter-frame modeling offers a more robust approach to RVOS.
  • MT-RVOS provides a significant advancement in maintaining object segmentation consistency in videos.