ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2410.01261
  4. Cited By
OCC-MLLM:Empowering Multimodal Large Language Model For the
  Understanding of Occluded Objects

OCC-MLLM:Empowering Multimodal Large Language Model For the Understanding of Occluded Objects

2 October 2024
Wenmo Qiu
Xinhan Di
    VLM
ArXivPDFHTML

Papers citing "OCC-MLLM:Empowering Multimodal Large Language Model For the Understanding of Occluded Objects"

2 / 2 papers shown
Title
CAPTURe: Evaluating Spatial Reasoning in Vision Language Models via Occluded Object Counting
CAPTURe: Evaluating Spatial Reasoning in Vision Language Models via Occluded Object Counting
Atin Pothiraj
Elias Stengel-Eskin
Jaemin Cho
Mohit Bansal
35
0
0
21 Apr 2025
OCC-MLLM-CoT-Alpha: Towards Multi-stage Occlusion Recognition Based on Large Language Models via 3D-Aware Supervision and Chain-of-Thoughts Guidance
OCC-MLLM-CoT-Alpha: Towards Multi-stage Occlusion Recognition Based on Large Language Models via 3D-Aware Supervision and Chain-of-Thoughts Guidance
Chaoyi Wang
Baoqing Li
Xinhan Di
MLLM
LRM
32
0
0
07 Apr 2025
1