4 papers · 1 filter
MulVec: Fine-Grained Role-Aware Matching for Training-Free Zero-Shot Composed Image Retrieval
Zihao Zhang, Dayan Wu, Xinze Liu +6
Training-free zero-shot composed image retrieval finds a target image in a gallery from a reference image and a text edit without learning from task-specific image triplets. Existi…
AdaptiveEmbed: Sample-Adaptive Multi-Vector Representation for Multimodal Retrieval
Xinze Liu, Lei Yang, Dayan Wu +7
Multi-vector representations have emerged as an effective paradigm for multimodal retrieval, representing each sample with multiple complementary embeddings to capture fine-grained…
Absorbing Gradient Conflicts: Modeling Semantic Variance via Kent Distributions for Cross-Modal Hashing
Hengjie Zhu, Dayan Wu, Zihao Zhang +5
Supervised proxy-based deep cross-modal hashing has become the dominant paradigm for large-scale retrieval. However, prevalent methods model class proxies as deterministic points i…
Beyond Post-Quantization: Native Hash Learning with a Dedicated HASH Token
Xinze Liu, Ding Wang, Dayan Wu +4
Efficient large-scale image retrieval requires compact representations that preserve semantic similarity under fast Hamming-space search. Deep hashing is appealing, but most existi…