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Works10 from public data
- 115
- Panoptic Video Scene Graph Generation73
A high-quality PVSG dataset is contributed, which consists of 400 videos (289 third-person + 111 egocentric videos) with totally 150K frames labeled with panoptic segmentation masks as well as fine, temporal scene graphs.
- Pair Then Relation: Pair-Net for Panoptic Scene Graph Generation36
A novel framework is presented: Pair then Relation (Pair-Net), which uses a Pair Proposal Network (PPN) to learn and filter sparse pair-wise relationships between subjects and objects and achieves over 10% absolute gains compared to the baseline, PSGFormer.
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- Generate Your Talking Avatar from Video Reference–
Talking Avatar generation from Video Reference (TAVR), a novel framework that shifts the paradigm by leveraging cross-scene video inputs and benefits from flexible inference-time video referencing and consistently surpasses existing baselines both quantitatively and qualitatively is introduced.
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- Knowledge Visualization: A Benchmark and Method for Knowledge-Intensive Text-to-Image Generation–
KVBench is introduced, a curriculum-grounded benchmark for evaluating knowledge-intensive T2I generation and KE-Check, a two-stage framework that improves scientific fidelity via Knowledge Elaboration for structured prompt enrichment and Checklist-Guided Refinement for explicit constraint enforcement through violation identification and constraint-guided editing.
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Publication data from OpenAlex; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-11. 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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