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- 4,660
- Beyond Part Models: Person Retrieval with Refined Part Pooling (and A Strong Convolutional Baseline)2,522
This paper targets at learning discriminative part-informed features for person retrieval and lays emphasis on the content consistency within each part, resulting in refined parts with enhanced within-part consistency.
- MARS: A Video Benchmark for Large-Scale Person Re-Identification1,088
It is shown that CNN in classification mode can be trained from scratch using the consecutive bounding boxes of each identity, and the learned CNN embedding outperforms other competing methods considerably and has good generalization ability on other video re-id datasets upon fine-tuning.
- Person Re-identification in the Wild830
A new dataset, PRW, is introduced to evaluate Person Re-identification in the Wild, and it is shown that pedestrian detection aids re-ID through two simple yet effective improvements: a cascaded fine-tuning strategy that trains a detection model first and then the classification model, and a Confidence Weighted Similarity (CWS) metric that incorporates detection scores into similarity measurement.
- SIFT Meets CNN: A Decade Survey of Instance Retrieval756
A comprehensive survey of instance retrieval over the last decade, presenting milestones in modern instance retrieval, reviews a broad selection of previous works in different categories, and provides insights on the connection between SIFT and CNN-based methods.
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- Packing and Padding: Coupled Multi-index for Accurate Image Retrieval223
A coupled Multi-Index (c-MI) framework to perform feature fusion at indexing level, which improves the retrieval accuracy significantly, while consuming only half of the query time compared to the baseline, and is well complementary to many prior techniques.
- GaussianEditor: Editing 3D Gaussians Delicately with Text Instructions220
A systematic framework to edit 3D scenes delicately via 3D Gaussians with text instructions, which can achieve more delicate and precise editing of 3D scenes than previous methods while enjoying much faster training speed, i.e. within 20 minutes on a single V100 GPU.
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- HalluciDoctor: Mitigating Hallucinatory Toxicity in Visual Instruction Data167
This work presents a novel hallucination detection and elimination framework, HalluciDoctor, based on the cross-checking paradigm, and uses this framework to identify and eliminate hallucinations in the training data automatically, and indicates that spurious correlations arising from long-tail object cooccurrences contribute to hallucinations.
- Discriminative coupled dictionary hashing for fast cross-media retrieval150
The experiments show that the DCDH and MV-DCDH outperform the state-of-the-art methods significantly on cross-media retrieval and conjecture that a balanced representation is crucial in cross- media retrieval.
- Building contextual visual vocabulary for large-scale image applications137
The experimental results show that the contextual visual vocabulary shows significant improvement over the classic visual vocabulary, and outperforms the state-of-the-art Bundled Feature in the terms of retrieval precision, memory consumption and efficiency.
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- Home photo content modeling for personalized event-based retrieval103
This work addresses the semantic gap between feature-based indexes computed automatically and human query and retrieval preferences and addresses the need for effective tools to organize and access photos in a semantically meaningful way.
- Scalar quantization for large scale image search97
The proposed scalar quantization achieves a relatively 42% improvement in mean average precision over the baseline (hierarchical visual vocabulary tree approach), and also outperforms the state-of-the-art Hamming Embedding approach and soft assignment method.
- Accurate Image Search with Multi-Scale Contextual Evidences92
This paper proposes to integrate discriminative cues from multiple contextual levels, i.e., local, regional, and global, via probabilistic analysis, and shows that CNN feature is complementary to SIFT due to its semantic awareness and compares favorably to several other descriptors such as GIST, HSV, etc.
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- Bayes Merging of Multiple Vocabularies for Scalable Image Retrieval82
This paper proposes a Bayes merging approach to down-weight the indexed features in the intersection set through explicitly modeling the correlation problem in a probabilistic view, and a joint similarity on both image- and feature-level is estimated for the indexed Features in the intersections set.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-15. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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