Papers › Robust Tracking against Adversarial Attacks

Robust Tracking against Adversarial Attacks

20 Jul 2020ECCV 2020 8arXiv:2007.09919archive 2025-07-28

Shuai Jia, Chao Ma, Yibing Song, Xiaokang Yang

While deep convolutional neural networks (CNNs) are vulnerable to adversarial attacks, considerably few efforts have been paid to construct robust deep tracking algorithms against adversarial attacks. Current studies on adversarial attack and defense mainly reside in a single image. In this work, we first attempt to generate adversarial examples on top of video sequences to improve the tracking robustness against adversarial attacks. To this end, we take temporal motion into consideration when generating lightweight perturbations over the estimated tracking results frame-by-frame. On one hand, we add the temporal perturbations into the original video sequences as adversarial examples to greatly degrade the tracking performance. On the other hand, we sequentially estimate the perturbations from input sequences and learn to eliminate their effect for performance restoration. We apply the proposed adversarial attack and defense approaches to state-of-the-art deep tracking algorithms. Extensive evaluations on the benchmark datasets demonstrate that our defense method not only eliminates the large performance drops caused by adversarial attacks, but also achieves additional performance gains when deep trackers are not under adversarial attacks.

PaperPDFConference PDFCodeCode Syntology ran

In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.

For agents, Syntology's MCP tool lists every function and class Syntology harvested from this paper and whether it ran (how to connect): get_harvested_code_for_paper(arxiv_id="2007.09919")

Code

Syntology Ran 5 of 6 code samples harvested from 2 repositories linked to this paper; 1 has no recorded run. Of those that ran: 2 ran · honoured contract; 3 ran · our draft was wrong.

By repository: official repository: 3 samples from 1 repository, 3 ran; community (archive-listed): 3 samples from 1 repository, 2 ran. The run record, sample by sample. “Ran” means executed on a synthesized input, not that the code is correct or reproduces the paper.

joshuajss/RTAA officialmentioned in papermentioned on GitHubpytorch report
vision-sjtu/rtaa mentioned on GitHubpytorchMIT report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

6 samples harvested; 5 ran; 2 honoured the contract we drafted; 1 has no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.

2ran · honoured contract
3ran · our draft was wrong
1unverified

Licence: 0 of the 6 samples are pointer only, meaning Syntology does not serve that copy's text. This page shows no code text for any sample; each one links to its file in the repository.

Harvested from 2 repositories linked to this paper, official or community; each sample names its own and says which. “Ran” means the sample executed on a synthesized input. It does not mean the output is correct, and nothing here reproduces the paper's results. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code.

Each sample ends with its code_sha256, Syntology's identity for that exact code. An agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

Repository labels, per sample. official repository: The archive marks this repository official for the paper. named in the paper: The archive records that the paper mentions this repository; it is not marked official. community (archive-listed): In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper. found in paper text by Syntology: Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted. community: Not in the archive's code links for this paper; a community repository Syntology harvested. Samples from a repository marked official are listed first. Licence labels name the repository's licence as recorded at harvest. “Pointer only” means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence label for the reason. File links open the file on GitHub at the default branch, which may have changed since the harvest.

generate_anchor joshuajss/RTAA/DaSiamRPN/code/run_SiamRPN.py official repository ran · our draft was wrong fingerprinted MIT (permissive) · ffd959a18529f028 · report
tracker_eval joshuajss/RTAA/DaSiamRPN/code/run_SiamRPN.py official repository ran · our draft was wrong MIT (permissive) · ac7f8214437637db · report
tracker_eval joshuajss/RTAA/DaSiamRPN/code/run_attack.py official repository ran · our draft was wrong MIT (permissive) · fd9e88b104e6b6f7 · report
to_numpy vision-sjtu/rtaa/DaSiamRPN/code/utils.py community (archive-listed) ran · honoured contract MIT (permissive) · b476623700945834 · report
to_torch vision-sjtu/rtaa/DaSiamRPN/code/utils.py community (archive-listed) ran · honoured contract MIT (permissive) · 7aac4c51e0ceee97 · report
im_to_numpy vision-sjtu/rtaa/DaSiamRPN/code/utils.py community (archive-listed) unverified MIT (permissive) · fec5535bc7550e01 · report

Tasks

Adversarial Attack

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections