Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-13T19:50:03.094100Z
Paper Citation Record · LEDGER
Drift-Resilient Temporal Priors for Visual Tracking
As of 4 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2604.02654.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+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
Reference resolution
54 of 54 outbound references displayed
- verified exact0
- verified fuzzy53
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 9464dd4a-b48b-4bb5-bba6-a9008f2aa61e · outbound
This paper cites Ar- trackv2: Prompting autoregressive tracker where to look and how to describe.
Drift-Resilient Temporal Priors for Visual Tracking Ar- trackv2: Prompting autoregressive tracker where to look and how to describe
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.219876Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c543b16f-b803-4d23-bba0-e712b0aa5a16 · outbound
This paper cites Learning discriminative model prediction for track- ing.
Drift-Resilient Temporal Priors for Visual Tracking Learning discriminative model prediction for track- ing
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.211788Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7edf3b67-ff4e-4798-b278-dfde5fdf5679 · outbound
This paper cites Hiptrack: Vi- sual tracking with historical prompts.
Drift-Resilient Temporal Priors for Visual Tracking Hiptrack: Vi- sual tracking with historical prompts
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.194942Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation bc56ce25-c695-4dd0-bf40-0647f376dea6 · outbound
This paper cites Spmtrack: Spatio-temporal parameter-efficient fine-tuning with mixture of experts for scalable visual tracking.
Drift-Resilient Temporal Priors for Visual Tracking Spmtrack: Spatio-temporal parameter-efficient fine-tuning with mixture of experts for scalable visual tracking
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.199104Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c9d22377-3032-4410-8665-8deacb74db90 · outbound
This paper cites Robust object modeling for visual tracking.
Drift-Resilient Temporal Priors for Visual Tracking Robust object modeling for visual tracking
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.190733Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4d217ec9-d563-42ec-9e21-6342f9aa49cb · outbound
This paper cites Backbone is all your need: A simplified architecture for visual object tracking.
Drift-Resilient Temporal Priors for Visual Tracking Backbone is all your need: A simplified architecture for visual object tracking
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.203381Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6f50cf80-2c63-476d-8025-01db68a5d257 · outbound
This paper cites Transformer tracking.
Drift-Resilient Temporal Priors for Visual Tracking Transformer tracking
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.223969Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a855dad8-821a-4a76-bda6-5c0c3e89a841 · outbound
This paper cites High-performance transformer tracking.
Drift-Resilient Temporal Priors for Visual Tracking High-performance transformer tracking
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.207354Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 00e88067-28d2-45dd-9bed-b45657bf2154 · outbound
This paper cites SeqTrack: Sequence to sequence learning for visual ob- ject tracking.
Drift-Resilient Temporal Priors for Visual Tracking SeqTrack: Sequence to sequence learning for visual ob- ject tracking
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.215692Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c8dd3f42-7fb9-4157-be8e-c9ebaa27a304 · outbound
This paper cites MixFormer: End-to-end tracking with iterative mixed atten- tion.
Drift-Resilient Temporal Priors for Visual Tracking MixFormer: End-to-end tracking with iterative mixed atten- tion
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.182563Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ec90b417-59f3-4353-9906-59cf0b2c06f4 · outbound
This paper cites MixFormer: End-to-end tracking with iterative mixed atten- tion.IEEE Transactions on Pattern Analysis and Machine Intelligence, pages 4129 – 4146.
Drift-Resilient Temporal Priors for Visual Tracking MixFormer: End-to-end tracking with iterative mixed atten- tion.IEEE Transactions on Pattern Analysis and Machine Intelligence, pages 4129 – 4146
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.187287Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 395fcb69-c833-4f6c-bac0-6912156e52f9 · outbound
This paper cites Proba- bilistic regression for visual tracking.
Drift-Resilient Temporal Priors for Visual Tracking Proba- bilistic regression for visual tracking
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.292661Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3c198bb5-54e9-492f-8301-e3d30041f78a · outbound
This paper cites FlashAttention-2: Faster attention with better par- allelism and work partitioning.
Drift-Resilient Temporal Priors for Visual Tracking FlashAttention-2: Faster attention with better par- allelism and work partitioning
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.296979Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 886c0c3a-67a7-466e-b504-861d3a605253 · outbound
This paper cites Fu, Stefano Ermon, Atri Rudra, and Christopher R´e.
Drift-Resilient Temporal Priors for Visual Tracking Fu, Stefano Ermon, Atri Rudra, and Christopher R´e
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.312727Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4fa3eb63-600f-4e95-b198-8bcf09fd30f9 · outbound
This paper cites Vision transformers need registers.
Drift-Resilient Temporal Priors for Visual Tracking Vision transformers need registers
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.240153Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6eaa3475-a74d-404f-b609-bbd78030feea · outbound
This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.
Drift-Resilient Temporal Priors for Visual Tracking An image is worth 16x16 words: Transformers for image recognition at scale
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.340134Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c61eeae9-dfbe-43b6-a61e-f10db6ae65d0 · outbound
This paper cites LaSOT: A high-quality benchmark for large-scale single ob- ject tracking.
Drift-Resilient Temporal Priors for Visual Tracking LaSOT: A high-quality benchmark for large-scale single ob- ject tracking
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.257177Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b5f8c625-c199-412e-9120-0b8e2ec571f6 · outbound
This paper cites AiATrack: Attention in attention for transformer visual tracking.
Drift-Resilient Temporal Priors for Visual Tracking AiATrack: Attention in attention for transformer visual tracking
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.304426Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b258765e-c6b6-4720-9036-fca0d24b8a6e · outbound
This paper cites Generalized relation modeling for transformer tracking.
Drift-Resilient Temporal Priors for Visual Tracking Generalized relation modeling for transformer tracking
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.228386Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b5bbedf3-beae-466d-bd0e-6bfb31ce6e04 · outbound
This paper cites Dreamtrack: Dreaming the future for mul- timodal visual object tracking.
Drift-Resilient Temporal Priors for Visual Tracking Dreamtrack: Dreaming the future for mul- timodal visual object tracking
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.358502Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0d5180fc-d2a9-4cdb-bcc0-5d91dd83f2fe · outbound
This paper cites Target-aware tracking with long-term context attention.
Drift-Resilient Temporal Priors for Visual Tracking Target-aware tracking with long-term context attention
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.232523Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation fb605278-c7ef-42ba-a120-99a21fadb0e4 · outbound
This paper cites LoRA: Low-rank adaptation of large language models.
Drift-Resilient Temporal Priors for Visual Tracking LoRA: Low-rank adaptation of large language models
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.403812Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation bf90354e-e21a-4f95-b810-181a4dda4ec5 · outbound
This paper cites Got-10k: A large high-diversity benchmark for generic object tracking in the wild.IEEE Transactions on Pattern Analysis and Ma- chine Intelligence, 43(5):1562–1577.
Drift-Resilient Temporal Priors for Visual Tracking Got-10k: A large high-diversity benchmark for generic object tracking in the wild.IEEE Transactions on Pattern Analysis and Ma- chine Intelligence, 43(5):1562–1577
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.382386Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 265b7444-bbfa-448d-8ec4-36f4a1869ab0 · outbound
This paper cites Rtracker: Recoverable tracking via pn tree structured memory.
Drift-Resilient Temporal Priors for Visual Tracking Rtracker: Recoverable tracking via pn tree structured memory
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.370197Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 877d8181-51a9-46c4-9fe6-af1927f9d594 · outbound
This paper cites Exploring enhanced contextual information for video-level object tracking.
Drift-Resilient Temporal Priors for Visual Tracking Exploring enhanced contextual information for video-level object tracking
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.330262Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 47fb7faf-40ec-4c3e-8fa2-c682bfaa156b · outbound
This paper cites The tenth visual object tracking vot2022 challenge re- sults.
Drift-Resilient Temporal Priors for Visual Tracking The tenth visual object tracking vot2022 challenge re- sults
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.365955Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 07727eaf-ece9-48c8-aafa-3d097ea46d1a · outbound
This paper cites The second visual object tracking segmentation vots2024 challenge results.
Drift-Resilient Temporal Priors for Visual Tracking The second visual object tracking segmentation vots2024 challenge results
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.326257Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e2e304c5-d7ed-4cae-959a-10c605eb1431 · outbound
This paper cites FractalNet: Ultra-deep neural networks without residuals.
Drift-Resilient Temporal Priors for Visual Tracking FractalNet: Ultra-deep neural networks without residuals
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.334331Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 89367ef9-458f-4eac-9fd7-717ba634f346 · outbound
This paper cites CiteTracker: Correlating image and text for visual tracking.
Drift-Resilient Temporal Priors for Visual Tracking CiteTracker: Correlating image and text for visual tracking
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.344272Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f374a86b-fa5e-4c50-80b9-b32fa7a5a32c · outbound
This paper cites SwinTrack: A simple and strong baseline for trans- former tracking.
Drift-Resilient Temporal Priors for Visual Tracking SwinTrack: A simple and strong baseline for trans- former tracking
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.271335Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 265e2ddc-95d7-4ff5-afaf-be11ac3efb96 · outbound
This paper cites Tracking meets lora: Faster training, larger model, stronger performance.
Drift-Resilient Temporal Priors for Visual Tracking Tracking meets lora: Faster training, larger model, stronger performance
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.244198Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 69838809-6161-4f5c-aef5-2b20654c0100 · outbound
This paper cites Loratv2: En- abling low-cost temporal modeling in one-stream trackers.
Drift-Resilient Temporal Priors for Visual Tracking Loratv2: En- abling low-cost temporal modeling in one-stream trackers
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.252637Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c6b8ed0b-e8fc-4052-b3eb-4fb7ca072209 · outbound
This paper cites Microsoft COCO: Common objects in context.
Drift-Resilient Temporal Priors for Visual Tracking Microsoft COCO: Common objects in context
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.279877Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8681e6c7-a00f-4785-8f0f-f8412750b53e · outbound
This paper cites Decoupled weight decay regularization.
Drift-Resilient Temporal Priors for Visual Tracking Decoupled weight decay regularization
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.275740Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 967371ae-95b9-40df-904d-3063e3125b0f · outbound
This paper cites A benchmark and simulator for uav tracking.
Drift-Resilient Temporal Priors for Visual Tracking A benchmark and simulator for uav tracking
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.374158Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation fe152e29-618b-449a-b01c-2a0a5ed97b21 · outbound
This paper cites TrackingNet: A large-scale dataset and benchmark for object tracking in the wild.
Drift-Resilient Temporal Priors for Visual Tracking TrackingNet: A large-scale dataset and benchmark for object tracking in the wild
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.362222Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 39165ac0-61c4-4eec-a9d1-41d5865ac35e · outbound
This paper cites Learning multi-domain convolutional neural networks for visual tracking.
Drift-Resilient Temporal Priors for Visual Tracking Learning multi-domain convolutional neural networks for visual tracking
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.394598Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 299cd1ac-5f60-4eba-ab2d-b7ce1bbc69f9 · outbound
This paper cites DINOv2: Learning robust visual features without supervi- sion.
Drift-Resilient Temporal Priors for Visual Tracking DINOv2: Learning robust visual features without supervi- sion
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.308554Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 07814236-9524-42bf-8819-52c411ba5f4f · outbound
This paper cites Vast- track: Vast category visual object tracking.
Drift-Resilient Temporal Priors for Visual Tracking Vast- track: Vast category visual object tracking
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.378368Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ee937aa5-6b7e-42bf-9640-f141a66bb86c · outbound
This paper cites Self-attention Does Not Need $O(n^2)$ Memory.
Drift-Resilient Temporal Priors for Visual Tracking Self-attention Does Not Need $O(n^2)$ Memory
Reference 40
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T19:53:11.800078Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 37f57161-8c2a-45f1-97ec-1f2a13d9e0c6 · outbound
This paper cites Generalized in- tersection over union: A metric and a loss for bounding box regression.
Drift-Resilient Temporal Priors for Visual Tracking Generalized in- tersection over union: A metric and a loss for bounding box regression
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.300590Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f78bc9eb-e2cf-47f6-a3e8-2a044b1fa440 · outbound
This paper cites DeiT III: Revenge of the ViT.
Drift-Resilient Temporal Priors for Visual Tracking DeiT III: Revenge of the ViT
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.317676Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b34eb598-4f6d-4aef-8bce-194ef2d0bf63 · outbound
This paper cites Towards more flexible and accurate object tracking with natural language: Algo- rithms and benchmark.
Drift-Resilient Temporal Priors for Visual Tracking Towards more flexible and accurate object tracking with natural language: Algo- rithms and benchmark
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.322285Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation daa4c3e8-c477-4b51-9167-6668d008d0ab · outbound
This paper cites Autoregressive visual tracking.
Drift-Resilient Temporal Priors for Visual Tracking Autoregressive visual tracking
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.348480Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e67782a8-84d6-46ae-9350-f5fec7a9c530 · outbound
This paper cites DropMAE: Masked autoen- coders with spatial-attention dropout for tracking tasks.
Drift-Resilient Temporal Priors for Visual Tracking DropMAE: Masked autoen- coders with spatial-attention dropout for tracking tasks
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.399854Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 973322e3-4970-4827-8443-1c819b8f1da2 · outbound
This paper cites Object track- ing benchmark.IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(9):1834–1848.
Drift-Resilient Temporal Priors for Visual Tracking Object track- ing benchmark.IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(9):1834–1848
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.283852Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation dd45768a-35cd-4545-a2f5-2ce89eea7fae · outbound
This paper cites Motiontrack: Learning motion predictor for multiple object tracking.Neu- ral Networks, 179:106539.
Drift-Resilient Temporal Priors for Visual Tracking Motiontrack: Learning motion predictor for multiple object tracking.Neu- ral Networks, 179:106539
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.248694Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation fa70c845-07ac-402d-818e-95ad240a0c7e · outbound
This paper cites Video- track: Learning to track objects via video transformer.
Drift-Resilient Temporal Priors for Visual Tracking Video- track: Learning to track objects via video transformer
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.262745Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 600097a5-a0fd-4b22-b19d-a3b6c640dbc0 · outbound
This paper cites Diffusiontrack: Point set diffusion model for visual object tracking.
Drift-Resilient Temporal Priors for Visual Tracking Diffusiontrack: Point set diffusion model for visual object tracking
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.288582Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3e8addb3-9b7e-4424-bfd8-f6ed1b4f5be3 · outbound
This paper cites Autore- gressive queries for adaptive tracking with spatio-temporal transformers.
Drift-Resilient Temporal Priors for Visual Tracking Autore- gressive queries for adaptive tracking with spatio-temporal transformers
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.352858Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8769a117-8c88-4f0a-9633-e98892ebc254 · outbound
This paper cites Learning spatio-temporal transformer for vi- sual tracking.
Drift-Resilient Temporal Priors for Visual Tracking Learning spatio-temporal transformer for vi- sual tracking
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.266828Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cf6a8b08-6880-4c6b-927a-23f0c631530d · outbound
This paper cites Joint feature learning and relation modeling for tracking: A one-stream framework.
Drift-Resilient Temporal Priors for Visual Tracking Joint feature learning and relation modeling for tracking: A one-stream framework
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.390382Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 536e3529-c68b-4d90-accb-9d4e7b59a4c0 · outbound
This paper cites Odtrack: Online dense temporal token learning for visual tracking.
Drift-Resilient Temporal Priors for Visual Tracking Odtrack: Online dense temporal token learning for visual tracking
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.386229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0bc83ae2-fe68-4fc3-9f90-58567346ee7d · outbound
This paper cites Two-stream beats one-stream: asymmetric siamese network for efficient visual tracking.
Drift-Resilient Temporal Priors for Visual Tracking Two-stream beats one-stream: asymmetric siamese network for efficient visual tracking
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-14T02:44:56.236253Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Pith citing papers
No inbound Pith citation observations are available.