SwePub
Tyck till om SwePub Sök här!
Sök i SwePub databas

  Utökad sökning

Träfflista för sökning "WFRF:(Li Li) ;mspu:(conferencepaper)"

Sökning: WFRF:(Li Li) > Konferensbidrag

  • Resultat 1-10 av 3167
Sortera/gruppera träfflistan
   
NumreringReferensOmslagsbildHitta
1.
  • Kristanl, Matej, et al. (författare)
  • The Seventh Visual Object Tracking VOT2019 Challenge Results
  • 2019
  • Ingår i: 2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW). - : IEEE COMPUTER SOC. - 9781728150239 ; , s. 2206-2241
  • Konferensbidrag (refereegranskat)abstract
    • The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOT-ST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2019 focused on long-term tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard short-term, long-term tracking and tracking with multi-channel imagery. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website(1).
  •  
2.
  • Kristan, Matej, et al. (författare)
  • The Sixth Visual Object Tracking VOT2018 Challenge Results
  • 2019
  • Ingår i: Computer Vision – ECCV 2018 Workshops. - Cham : Springer Publishing Company. - 9783030110086 - 9783030110093 ; , s. 3-53
  • Konferensbidrag (refereegranskat)abstract
    • The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis and a “real-time” experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. A long-term tracking subchallenge has been introduced to the set of standard VOT sub-challenges. The new subchallenge focuses on long-term tracking properties, namely coping with target disappearance and reappearance. A new dataset has been compiled and a performance evaluation methodology that focuses on long-term tracking capabilities has been adopted. The VOT toolkit has been updated to support both standard short-term and the new long-term tracking subchallenges. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website (http://votchallenge.net).
  •  
3.
  • Kristan, Matej, et al. (författare)
  • The first visual object tracking segmentation VOTS2023 challenge results
  • 2023
  • Ingår i: 2023 IEEE/CVF International conference on computer vision workshops (ICCVW). - : Institute of Electrical and Electronics Engineers Inc.. - 9798350307443 - 9798350307450 ; , s. 1788-1810
  • Konferensbidrag (refereegranskat)abstract
    • The Visual Object Tracking Segmentation VOTS2023 challenge is the eleventh annual tracker benchmarking activity of the VOT initiative. This challenge is the first to merge short-term and long-term as well as single-target and multiple-target tracking with segmentation masks as the only target location specification. A new dataset was created; the ground truth has been withheld to prevent overfitting. New performance measures and evaluation protocols have been created along with a new toolkit and an evaluation server. Results of the presented 47 trackers indicate that modern tracking frameworks are well-suited to deal with convergence of short-term and long-term tracking and that multiple and single target tracking can be considered a single problem. A leaderboard, with participating trackers details, the source code, the datasets, and the evaluation kit are publicly available at the challenge website1
  •  
4.
  • Kristan, Matej, et al. (författare)
  • The Visual Object Tracking VOT2015 challenge results
  • 2015
  • Ingår i: Proceedings 2015 IEEE International Conference on Computer Vision Workshops ICCVW 2015. - : IEEE. - 9780769557205 ; , s. 564-586
  • Konferensbidrag (refereegranskat)abstract
    • The Visual Object Tracking challenge 2015, VOT2015, aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 62 trackers are presented. The number of tested trackers makes VOT 2015 the largest benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the appendix. Features of the VOT2015 challenge that go beyond its VOT2014 predecessor are: (i) a new VOT2015 dataset twice as large as in VOT2014 with full annotation of targets by rotated bounding boxes and per-frame attribute, (ii) extensions of the VOT2014 evaluation methodology by introduction of a new performance measure. The dataset, the evaluation kit as well as the results are publicly available at the challenge website(1).
  •  
5.
  • Kristan, Matej, et al. (författare)
  • The Visual Object Tracking VOT2016 Challenge Results
  • 2016
  • Ingår i: COMPUTER VISION - ECCV 2016 WORKSHOPS, PT II. - Cham : SPRINGER INT PUBLISHING AG. - 9783319488813 - 9783319488806 ; , s. 777-823
  • Konferensbidrag (refereegranskat)abstract
    • The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 70 trackers are presented, with a large number of trackers being published at major computer vision conferences and journals in the recent years. The number of tested state-of-the-art trackers makes the VOT 2016 the largest and most challenging benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the Appendix. The VOT2016 goes beyond its predecessors by (i) introducing a new semi-automatic ground truth bounding box annotation methodology and (ii) extending the evaluation system with the no-reset experiment.
  •  
6.
  • Bhat, Goutam, et al. (författare)
  • NTIRE 2022 Burst Super-Resolution Challenge
  • 2022
  • Ingår i: 2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW 2022). - : IEEE. - 9781665487399 - 9781665487405 ; , s. 1040-1060
  • Konferensbidrag (refereegranskat)abstract
    • Burst super-resolution has received increased attention in recent years due to its applications in mobile photography. By merging information from multiple shifted images of a scene, burst super-resolution aims to recover details which otherwise cannot be obtained using a simple input image. This paper reviews the NTIRE 2022 challenge on burst super-resolution. In the challenge, the participants were tasked with generating a clean RGB image with 4x higher resolution, given a RAW noisy burst as input. That is, the methods need to perform joint denoising, demosaicking, and super-resolution. The challenge consisted of 2 tracks. Track 1 employed synthetic data, where pixel-accurate high-resolution ground truths are available. Track 2 on the other hand used real-world bursts captured from a handheld camera, along with approximately aligned reference images captured using a DSLR. 14 teams participated in the final testing phase. The top performing methods establish a new state-of-the-art on the burst super-resolution task.
  •  
7.
  • Felsberg, Michael, et al. (författare)
  • The Thermal Infrared Visual Object Tracking VOT-TIR2015 Challenge Results
  • 2015
  • Ingår i: Proceedings of the IEEE International Conference on Computer Vision. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781467383905 ; , s. 639-651
  • Konferensbidrag (refereegranskat)abstract
    • The Thermal Infrared Visual Object Tracking challenge 2015, VOTTIR2015, aims at comparing short-term single-object visual trackers that work on thermal infrared (TIR) sequences and do not apply prelearned models of object appearance. VOT-TIR2015 is the first benchmark on short-term tracking in TIR sequences. Results of 24 trackers are presented. For each participating tracker, a short description is provided in the appendix. The VOT-TIR2015 challenge is based on the VOT2013 challenge, but introduces the following novelties: (i) the newly collected LTIR (Linköping TIR) dataset is used, (ii) the VOT2013 attributes are adapted to TIR data, (iii) the evaluation is performed using insights gained during VOT2013 and VOT2014 and is similar to VOT2015.
  •  
8.
  • Felsberg, Michael, 1974-, et al. (författare)
  • The Thermal Infrared Visual Object Tracking VOT-TIR2016 Challenge Results
  • 2016
  • Ingår i: Computer Vision – ECCV 2016 Workshops. ECCV 2016.. - Cham : SPRINGER INT PUBLISHING AG. - 9783319488813 - 9783319488806 ; , s. 824-849
  • Konferensbidrag (refereegranskat)abstract
    • The Thermal Infrared Visual Object Tracking challenge 2016, VOT-TIR2016, aims at comparing short-term single-object visual trackers that work on thermal infrared (TIR) sequences and do not apply pre-learned models of object appearance. VOT-TIR2016 is the second benchmark on short-term tracking in TIR sequences. Results of 24 trackers are presented. For each participating tracker, a short description is provided in the appendix. The VOT-TIR2016 challenge is similar to the 2015 challenge, the main difference is the introduction of new, more difficult sequences into the dataset. Furthermore, VOT-TIR2016 evaluation adopted the improvements regarding overlap calculation in VOT2016. Compared to VOT-TIR2015, a significant general improvement of results has been observed, which partly compensate for the more difficult sequences. The dataset, the evaluation kit, as well as the results are publicly available at the challenge website.
  •  
9.
  • Kristan, Matej, et al. (författare)
  • The Ninth Visual Object Tracking VOT2021 Challenge Results
  • 2021
  • Ingår i: 2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW 2021). - : IEEE COMPUTER SOC. - 9781665401913 ; , s. 2711-2738
  • Konferensbidrag (refereegranskat)abstract
    • The Visual Object Tracking challenge VOT2021 is the ninth annual tracker benchmarking activity organized by the VOT initiative. Results of 71 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in recent years. The VOT2021 challenge was composed of four sub-challenges focusing on different tracking domains: (i) VOT-ST2021 challenge focused on short-term tracking in RGB, (ii) VOT-RT2021 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2021 focused on long-term tracking, namely coping with target disappearance and reappearance and (iv) VOT-RGBD2021 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2021 dataset was refreshed, while VOT-RGBD2021 introduces a training dataset and sequestered dataset for winner identification. The source code for most of the trackers, the datasets, the evaluation kit and the results along with the source code for most trackers are publicly available at the challenge website(1).
  •  
10.
  • Ding, C., et al. (författare)
  • Study on fracture of the fibrous monolith cemented carbide
  • 2013
  • Ingår i: Advanced Materials Research. - 1662-8985 .- 1022-6680. ; 815, s. 43-47
  • Konferensbidrag (refereegranskat)abstract
    • A fibrous monolith cemented carbide with WC-6%Co as cell and WC-20%Co as cell boundaries was produced through hot co-extrusion process in this paper. The density, hardness, transverse rupture strength (TRS) and fracture toughness (KIc) of the fibrous monolith cemented carbide were tested, and the fracture and crack propagation were observed by metalloscope and Scanning Electron Microscope. The result shows fibrous monolith structure design could effectively improve the TRS and the KIc of WC/Co cemented carbide without a significant decrease of hardness. It is the reason of high transverse rupture strength and fracture toughness that WC-20%Co can absorb more fracture energy in order to slow, prevent, or deflect crack propagation, proved by metalloscope and scanning electron microscope.
  •  
Skapa referenser, mejla, bekava och länka
  • Resultat 1-10 av 3167
Typ av publikation
konstnärligt arbete (5)
Typ av innehåll
refereegranskat (2324)
övrigt vetenskapligt/konstnärligt (835)
populärvet., debatt m.m. (8)
Författare/redaktör
Zheng, Li-Rong (155)
Li, J. (145)
Li, Haibo (92)
Li, Y. (82)
Li, Jian (81)
Tenhunen, Hannu (78)
visa fler...
Li, X. (63)
Zhang, Shi-Li (55)
Li, Hailong, 1976- (48)
Yang, Li (40)
Stoica, Peter (39)
Li, D. (35)
Li, H. (34)
Li, Jiebing (34)
Lu, Zhonghai (33)
Li, Zhongshan (30)
Li, L. (29)
Li, Z (29)
Popov, Sergei (29)
Li, N (29)
Li, Hui (29)
Guo, Li (29)
Zou, Zhuo (29)
Li, Hailong (29)
Wang, Shu Min, 1963 (28)
Chen, Qiang (28)
Yan, Jinyue (28)
Li, Xin-Hai (28)
Li, Qiang (28)
Li, Jingya, 1986 (28)
Svensson, Tommy, 197 ... (27)
Li, Ying (27)
Li, T. (27)
Li, G. (26)
Li, Shuo (26)
Li, C. (25)
Qiu, Min (25)
Li, Zhiyuan, 1974 (25)
Li, W. (24)
Stoica, Peter, 1949- (24)
Li, Dan, 1990 (24)
Li, S. (23)
Aldén, Marcus (23)
Li, YH (23)
Ringsberg, Jonas, 19 ... (23)
Yan, Jinyue, 1959- (23)
Li, Wei (22)
Lau, Buon Kiong (22)
He, Sailing (22)
Jonsson, Fredrik (22)
visa färre...
Lärosäte
Kungliga Tekniska Högskolan (904)
Karolinska Institutet (510)
Chalmers tekniska högskola (399)
Uppsala universitet (308)
Lunds universitet (257)
Linköpings universitet (177)
visa fler...
Umeå universitet (140)
RISE (114)
Mälardalens universitet (98)
Luleå tekniska universitet (83)
Stockholms universitet (55)
Göteborgs universitet (37)
Malmö universitet (36)
Linnéuniversitetet (32)
Högskolan i Borås (31)
Mittuniversitetet (25)
Sveriges Lantbruksuniversitet (24)
Örebro universitet (22)
Högskolan Väst (20)
VTI - Statens väg- och transportforskningsinstitut (19)
Högskolan i Gävle (18)
Karlstads universitet (16)
Högskolan i Skövde (15)
Högskolan Dalarna (14)
Jönköping University (11)
Högskolan i Halmstad (10)
Blekinge Tekniska Högskola (10)
Högskolan Kristianstad (4)
Södertörns högskola (4)
Konstfack (1)
Handelshögskolan i Stockholm (1)
visa färre...
Språk
Engelska (3149)
Svenska (16)
Kinesiska (2)
Forskningsämne (UKÄ/SCB)
Teknik (1553)
Naturvetenskap (801)
Samhällsvetenskap (99)
Medicin och hälsovetenskap (80)
Lantbruksvetenskap (27)
Humaniora (18)

År

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy