Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
DA-Ada: Learning Domain-Aware Adapter for Domain Adaptive Object Detection
Authors: Haochen Li, Rui Zhang, Hantao Yao, Xin Zhang, Yifan Hao, Xinkai Song, Xiaqing Li, Yongwei Zhao, Yunji Chen, Ling Li
NeurIPS 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Comprehensive experiments over multiple DAOD tasks show that DA-Ada can efficiently infer a domain-aware visual encoder for boosting domain adaptive object detection. |
| Researcher Affiliation | Academia | 1Intelligent Software Research Center, Institute of Software, CAS, Beijing, China 2State Key Lab of Processors, Institute of Computing Technology, CAS, Beijing, China 3 State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, CAS, Beijing, China 4 University of Chinese Academy of Sciences, Beijing, China |
| Pseudocode | No | The paper provides block diagrams and mathematical equations in Figure 2, but does not present pseudocode or a clearly labeled algorithm block. |
| Open Source Code | Yes | Our code is available at https://github.com/Therock90421/DA-Ada. |
| Open Datasets | Yes | Cityscapes [9] contains diverse street scenes captured by a mobile camera in daylight. The regular partition consists of 2,975 training and 500 validation images annotated with eight classes. Foggy Cityscapes [54] simulates three distinct densities of fog on Cityscapes, containing 8,925 training images and 1,500 validation images. |
| Dataset Splits | Yes | Cityscapes [9] contains diverse street scenes captured by a mobile camera in daylight. The regular partition consists of 2,975 training and 500 validation images annotated with eight classes. Foggy Cityscapes [54] simulates three distinct densities of fog on Cityscapes, containing 8,925 training images and 1,500 validation images. |
| Hardware Specification | Yes | All experiments are deployed on 8 Tesla V100 GPUs. |
| Software Dependencies | No | The paper mentions using Region CLIP (ResNet-50) and Faster-RCNN, and the SGD optimizer, but does not provide specific version numbers for software libraries or programming languages used (e.g., Python, PyTorch, CUDA versions). |
| Experiment Setup | Yes | The hyperparameter λdia, λdita, λdec is set to 0.1, 1.0 and 0.1, respectively. We set the batch size of each domain to 8 and use the SGD optimizer with a warm-up learning rate. Mean Average Precision (m AP) with a threshold of 0.5 is taken as the evaluation metric. |