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Gangyan Zeng

7 papers at tracked venues · 6 at CORE A* · active 20242025

Venues

Frequent coauthors

Papers

  1. CLIP is Almost All You Need: Towards Parameter-Efficient Scene Text Retrieval without OCR
  2. Gather and Trace: Rethinking Video TextVQA from an Instance-oriented Perspective
  3. PerturbCTC: Improving Alignment in Scene Text Recognition with Feature Perturbation Based CTC
  4. Towards Natural Language-Based Document Image Retrieval: New Dataset and Benchmark
  5. Track the Answer: Extending TextVQA from Image to Video with Spatio-Temporal Clues
  6. When Semantics Mislead Vision: Mitigating Large Multimodal Models Hallucinations in Scene Text Spotting and Understanding
  7. Focus, Distinguish, and Prompt: Unleashing CLIP for Efficient and Flexible Scene Text Retrieval
    ACM MM 2024 · Gangyan Zeng