Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T04:21:07.783291Z
Paper Citation Record · LEDGER
As of 12 August 2026, this Paper Citation Record lists 81 of 81 outbound references and 0 inbound Pith citation observations for arXiv:2412.01556.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T04:21:07.783291Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
81 of 81 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 7090a0af-a775-43ab-acd3-8ef451166b47 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Multi-modal interactive attention and dual progressive decoding network for RGB-D/T salient object detection,
Reference 1
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3c48cd6b-d683-431c-8678-0ab69c2ef63f · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Multi-interactive dual- decoder for rgb-thermal salient object detection,
Reference 2
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 6ffe8057-5a7d-49ef-9537-36e738979610 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection A novel multiresolution spatiotemporal saliency detection model and its applications in image and video compression,
Reference 3
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation ec07f214-f600-46b5-b0ec-c1a606e48ebb · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Saliency-aware video object segmentation,
Reference 4
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 6f80ac6a-661e-4426-9356-3961fde4b095 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Non-rigid object tracking via deep multi-scale spatial-temporal discriminative saliency maps,
Reference 5
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 2724141b-01aa-4634-a46d-3deb6679c945 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Context disentan- gling and prototype inheriting for robust visual grounding,
Reference 6
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation c40e7b45-a490-475a-816c-206287a4f0db · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Salient object detection: A survey,
Reference 7
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 123c13cf-9b90-4ddf-b7ad-142cb7b8a869 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Salient object detection in the deep learning era: An in-depth survey,
Reference 8
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 7527f0df-b29a-43a2-aee0-7548b51d6337 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Rethinking RGB-D salient object detection: Models, data sets, and large-scale benchmarks,
Reference 9
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation f983a047-cf65-42e1-bcd8-3c865470c3b1 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection RGB-D salient object detection: A survey,
Reference 10
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 314f45d7-d60e-4b0a-a77a-8ddc7092254d · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Robust RGB-D fusion for saliency detection,
Reference 11
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation cd599fa1-1ceb-4dd4-b5ae-6e42dae56485 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Siamese network for RGB-D salient object detection and beyond,
Reference 12
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 934ba702-bc13-42b9-b510-1ced2fbb99cc · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Depth quality- inspired feature manipulation for efficient RGB-D salient object detection,
Reference 13
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation c316c76b-2d03-4955-a18d-fe0982048aba · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection RGB-T saliency detection benchmark: Dataset, baselines, analysis and a novel approach,
Reference 14
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 151308cd-0028-457f-b67f-8aa9bfd7ac28 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Rtfnet: Rgb-thermal fusion network for semantic segmentation of urban scenes,
Reference 15
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation b7586dcc-424f-4dce-bce1-eb2230f86824 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection RGBT Salient Object Detection: A Large-scale Dataset and Benchmark
Reference 16
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 949d7dd0-d842-4ca7-8c8f-49c6c98482e4 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Efficient context- guided stacked refinement network for rgb-t salient object detec- tion,
Reference 17
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 9fb18c78-d29e-43c4-a287-68d30a39e432 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Ecffnet: Effective and consistent feature fusion network for rgb-t salient object detection,
Reference 18
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 78396864-21a3-4afb-8d9a-1a7b6c540b51 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Cgfnet: Cross- guided fusion network for RGB-T salient object detection,
Reference 19
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 9de37536-9ce4-4788-b30f-7c3a5369dc62 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Unresolved cited work
Reference 20
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 1c717849-4483-4a2d-badd-31097a84ae8a · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Separate visual pathways for perception and action,
Reference 21
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 04f763bf-3458-4164-97ee-6629edbc9eee · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Cognitive neuroscience: feedback for natural visual stimuli,
Reference 22
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation d02155b3-131a-454c-9b17-ab13d309d44f · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection RGB-T image saliency detection via collaborative graph learning,
Reference 23
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 68df21e4-a18b-4c40-b5ff-26755b52c438 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Saliency detection via dense and sparse reconstruction,
Reference 24
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation ad7a68c4-6c11-4e79-937e-c8b081a0b8f5 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Global contrast based salient region detection,
Reference 25
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 0f4fb204-3e90-4c5c-ab17-0e16f53e54aa · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Salient object detection: A discriminative regional feature integration approach,
Reference 26
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation c14b1e33-979a-4d68-b61b-8d547feeb384 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Submodular salient region detection,
Reference 27
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1348d898-d5f7-40ef-a3af-d9e5d86caec3 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Saliency optimization from robust background detection,
Reference 28
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 2279156b-263a-4ecb-b310-d85b02da1974 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Salient region detection via integrating diffusion-based compactness and local contrast,
Reference 29
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation fec76941-adbc-4a58-8137-49d30394218c · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Very deep convolutional networks for large-scale image recognition,
Reference 30
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1f9dd3bc-328f-4d9e-82f1-538fc3ef90ae · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Deep residual learning for image recognition,
Reference 31
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d770648b-b034-45a9-82d7-d39955c82771 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Deeply supervised salient object detection with short connections,
Reference 32
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 058910a7-4b75-437d-8a5e-2ce4f6ce54aa · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Progressive attention guided recurrent network for salient object detection,
Reference 33
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation d63cf4fa-5034-47c0-948d-b13e78f94937 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Res2net: A new multi-scale backbone architecture,
Reference 34
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation c2fcdd4c-5c33-47ea-9f36-c89add8fcf0b · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Cascaded partial decoder for fast and accurate salient object detection,
Reference 35
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation c57f9517-b5e6-4702-85d2-6b7481abbc69 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection F3net: Fusion, feedback and focus for salient object detection,
Reference 36
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation fdbdeabf-61bc-487e-853c-2305b4025769 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Global context-aware progressive aggregation network for salient object detection,
Reference 37
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 70aaa720-a600-4380-9346-7063eeb8bd99 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Label decoupling framework for salient object detection,
Reference 38
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 10134b90-00e4-4d12-a49d-8968f60ffa67 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Auto-msfnet: Search multi-scale fusion network for salient object detection,
Reference 39
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 23f3bec7-13a7-44fc-8516-186e8e579b8f · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Multi-scale interactive network for salient object detection,
Reference 40
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 74de52c7-2c9c-42f4-9b59-9deac7f49318 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Cross-modality discrepant interaction network for RGB-D salient object detection,
Reference 41
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation ffbcbbb8-a08b-4488-bed7-82475009af3d · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Learning discriminative cross- modality features for RGB-D saliency detection,
Reference 42
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation a35e1954-6a19-4a10-b9e2-eb7c8c393e9e · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection M3s-nir: Multi-modal multi-scale noise-insensitive ranking for rgb-t saliency detection,
Reference 43
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation a6d8c1da-b853-4691-80e8-a0b326e96e23 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Learning multiscale deep features and SVM regressors for adaptive RGB-T saliency detection,
Reference 44
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation f8097fb0-84ff-4700-ba5d-4a5765057ab8 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection RGB-T salient object detection via fusing multi-level CNN features,
Reference 45
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 9ce8eb04-4dce-4e48-ab3b-a679b39ebbd2 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Revisiting feature fusion for RGB-T salient object detection,
Reference 46
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 1934a666-adde-46f6-afa0-ecabf2dcffa1 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Specificity- preserving RGB-D saliency detection,
Reference 47
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation e0039751-747d-4fa3-a2cf-2f19bd5bba54 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Cir-net: Cross-modality interaction and refinement for RGB-D salient object detection,
Reference 48
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 575cc98a-d8e8-4080-b5ed-625ab452096c · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Unresolved cited work
Reference 49
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f64ea89a-730a-4be7-a5e4-6fed76a5ba55 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Segregation of form, color, move- ment, and depth: anatomy, physiology, and perception,
Reference 50
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 7b952501-cdfa-4a73-877f-abd5ef9b91aa · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection CBAM: convolutional block attention module,
Reference 51
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 30b1d5ee-c670-409b-87d3-0ea944a1f15a · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Ctnet: Context-based tandem network for semantic segmentation,
Reference 52
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 997e87ab-f9cd-4656-9c58-c6d4c9f0fe2f · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection A tutorial on the cross-entropy method,
Reference 53
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation a350a1de-661f-4f28-b894-12e8124c4e52 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Deeproadmapper: Extracting road topology from aerial images,
Reference 54
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation e5d35f33-869e-4b90-85eb-e84ea48faf33 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Swin transformer: Hierarchical vision transformer using shifted windows,
Reference 55
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 0eb8e49c-109d-445c-95a8-ebc503c3fda7 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Learning selective self-mutual attention for RGB-D saliency detection,
Reference 56
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 5ba86826-4668-475f-86c3-7fb424cd8994 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection JL-DCF: joint learning and densely-cooperative fusion framework for RGB-D salient object detection,
Reference 57
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 7572c992-6e52-4850-80fa-1a843af3b9c9 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Hierarchical alternate interaction network for RGB-D salient object detection,
Reference 58
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation c0f2b177-74f2-47c5-9037-518f884809ea · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Three-stage bidirectional interaction network for efficient RGB-D salient object detection,
Reference 59
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 5385eb11-4b04-4a81-87b3-53a9d90527b6 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Source-free depth for object pop-out,
Reference 60
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation c9eb1033-5198-4b3b-8f0d-59d153a8ce88 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Hidanet: RGB-D salient object detection via hierarchical depth awareness,
Reference 61
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation b12f7f82-0c95-4f98-b37c-83ed8138f92c · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Unified information fusion network for multi-modal RGB-D and RGB-T salient object detection,
Reference 62
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 80a090c8-2ace-4989-b6ed-ded04f4b1047 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Real-time one-stream semantic-guided refinement network for rgb-thermal salient object detection,
Reference 63
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 21f37bd4-432e-4372-a3d4-d8d228c50501 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Lsnet: Lightweight spatial boosting network for detecting salient objects in rgb-thermal images,
Reference 64
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation b2a8e6f5-abdf-40ab-83d4-fde9e145a656 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection CAVER: cross-modal view- mixed transformer for bi-modal salient object detection,
Reference 65
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 0b41c6bb-2bf1-4dd0-b8f7-d7f8fe4e5f72 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Tritransnet: RGB- D salient object detection with a triplet transformer embedding network,
Reference 66
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation b8e595d2-c957-4fe3-b913-abe7814a20c9 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Swinnet: Swin transformer drives edge-aware RGB-D and RGB-T salient object detection,
Reference 67
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation c97def86-ce01-4685-bfb7-d342743484ba · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Hrtransnet: Hrformer-driven two-modality salient object detection,
Reference 68
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 832f0844-c0b9-468d-909c-c8146cf849b1 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Object segmentation by mining cross-modal semantics,
Reference 69
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 23a44451-8628-4e07-82c5-732bead5165a · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Bag of tricks for image classification with convolutional neural networks,
Reference 70
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Observation 7da64870-eccf-4a50-be25-cef3bb7c14ac · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection An image is worth 16x16 words: Transformers for image recognition at scale,
Reference 71
Source-reported events for the cited work
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Observation 96462359-9ff8-41b9-abdf-f8e0bf23406f · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Hrformer: High-resolution vision transformer for dense predict,
Reference 72
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 84dcaa59-8940-4244-ab7a-b86c622f7d8e · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Target-aware dual adversarial learning and a multi-scenario multi-modality benchmark to fuse infrared and visible for object detection,
Reference 73
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation ad36a6ef-7210-4fbc-8e04-58dcd1e99fba · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Structure-measure: A new way to evaluate foreground maps,
Reference 74
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 089037f8-bdda-4f46-92aa-5aed07d374ec · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Frequency-tuned salient region detection,
Reference 75
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 7d31f87d-23f4-442e-978b-8712767fb313 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection How to evaluate foreground maps,
Reference 76
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 730ee93a-3008-4d79-a516-7b9c579538c8 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Enhanced- alignment measure for binary foreground map evaluation,
Reference 77
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation f5c95e13-5641-460c-8b91-8e033ff5955c · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Saliency filters: Contrast based filtering for salient region detection,
Reference 78
Source-reported events for the cited work
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Observation d612d1d4-02fc-4ba1-9779-f822da9ed046 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Imagenet large scale visual recognition challenge,
Reference 79
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation c78813a2-e857-4979-babd-737d268730b1 · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Pyramid scene parsing network,
Reference 80
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 1b893678-9149-4ec9-b88b-e4d6ca1babaf · outbound
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs,
Reference 81
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
No inbound Pith citation observations are available.