QuRe: Query-Relevant Retrieval through Hard Negative Sampling in Composed Image Retrieval
Authors: Jaehyun Kwak, Ramahdani Muhammad Izaaz Inhar, Se-Young Yun, Sung-Ju Lee
ICML 2025 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments demonstrate that QURE achieves stateof-the-art performance on Fashion IQ and CIRR datasets while exhibiting the strongest alignment with human preferences on the HP-Fashion IQ dataset. |
| Researcher Affiliation | Academia | 1KAIST. Correspondence to: Sung-Ju Lee <EMAIL>. |
| Pseudocode | Yes | Algorithm 1 Training Flow of QURE |
| Open Source Code | Yes | The source code is available at https: //github.com/jackwaky/Qu Re. |
| Open Datasets | Yes | We evaluate the models on widely used CIR datasets, Fashion IQ (Wu et al., 2021) and CIRR (Suhr et al., 2018), to assess their ability to retrieve the target image. |
| Dataset Splits | Yes | We evaluate the models on widely used CIR datasets, Fashion IQ (Wu et al., 2021) and CIRR (Suhr et al., 2018), to assess their ability to retrieve the target image. Additionally, we evaluate them on the HP-Fashion IQ dataset to assess their alignment with human preferences. ... We selected the Fashion IQ dataset for its high relevance and broad applicability, mirroring the search functionalities of e-commerce platforms. |
| Hardware Specification | Yes | All experiments were conducted using a single Nvidia RTX 3090 GPU. |
| Software Dependencies | No | No specific software dependencies with version numbers are mentioned in the paper, beyond the use of BLIP-2 as a backbone model and AdamW optimizer. |
| Experiment Setup | Yes | QURE is trained using the Adam W optimizer (Loshchilov, 2017) for 50 epochs on CIRR and 30 epochs on Fashion IQ. The hard negative set H was defined ndef times, starting with a warm-up phase where H initially included the entire corpus except for the target during the first nepoch/ndef epochs. The hard negative set H is updated every nepoch/ndef epochs. We set ndef to six for both Fashion IQ and CIRR. ... We resized images to 224 224 with a 1.25 padding ratio. |