Good Papers

Showing papers from Queen Mary University of London / Huawei Research Finland Show all papers

57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026Queen Mary, University of LondonNational Technical University ofQueen Mary University of London Video understanding

Behaviour4All: A Dependency-Aware Toolkit for in-the-wild Facial Behaviour Analysis

Dimitrios Kollias, Chunchang Shao, Odysseus Kaloidas, Ioannis Patras

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Queen Mary University of LondonHuawei Technologies Ltd.UCLU BedfordshireQueen Mary University of London LLM evaluation & benchmarks

CADMA: Capacity-Aware Recall Decomposition for Generative Model Assessment

Debin Meng, Zheng Gao, Ziquan Liu, Yanran Li and 2 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Queen Mary, University of LondonSoutheastU the Bundeswehr MunichQueen Mary University of LondonNanjing University of Science anVideo understanding

ViewSAM: Learning View-aware Semantics for Weakly Supervised Cross-view Referring Multi-Object Tracking

Jiawei Ge, Xintian Zhang, Jiuxin Cao, Bo Liu and 8 more

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5