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402        <div class="container is-max-desktop">
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404            <div class="column has-text-centered">
405              <h1 class="title is-1 publication-title">EmoVid: A Multimodal Emotion Video Dataset for Emotion-Centric
406                Video Understanding and Generation</h1>
407              <div class="is-size-5 publication-authors" style="margin-top:0.5rem;">
408                <span class="author-block"><a href="https://zane-zyqiu.github.io" target="_blank"
409                    rel="noopener">Zongyang Qiu</a><sup>*</sup>,</span>
410                <span class="author-block"><a href="https://cislab.hkust-gz.edu.cn/members/bingyuan-wang"
411                    target="_blank" rel="noopener">Bingyuan Wang</a><sup>*</sup>,</span>
412                <span class="author-block"><a href="https://github.com/May-apple" target="_blank" rel="noopener">Xingbei
413                    Chen</a>,</span>
414                <span class="author-block"><a href="https://yingqinghe.github.io" target="_blank"
415                    rel="noopener">Yingqing He</a>,</span>
416                <span class="author-block"><a href="https://cislab.hkust-gz.edu.cn/members/zeyu-wang" target="_blank"
417                    rel="noopener">Zeyu Wang</a><sup>†</sup></span>
418              </div>
419
420              <div class="is-size-5 publication-authors" style="margin-top:0.25rem;">
421                <span class="author-block">HKUST(GZ)</span>
422                <span class="author-block">Fudan University</span>
423                <span class="author-block">HKUST</span><br>
424                <span class="author-block">AAAI 2026 Oral</span>
425                <span class="eql-cntrb"><small><br><sup>*</sup>Indicates Equal Contribution, <sup>†</sup>Corresponding Author</small></span>
426              </div>
427
428              <div class="column has-text-centered" style="margin-top:0.75rem;">
429                <div class="publication-links">
430                  <span class="link-block">
431                    <a href="https://www.arxiv.org/abs/2511.11002" target="_blank" rel="noopener"
432                      class="external-link button is-normal is-rounded is-dark">
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434                        <i class="fas fa-file-pdf"></i>
435                      </span>
436                      <span>Paper</span>
437                    </a>
438                  </span>
439
440                  <span class="link-block">
441                    <a href="https://docs.google.com/forms/d/e/1FAIpQLSekp08DeWKxSbwEMkor1wIyubcqFfUwTEvCVpTlW1pga3pqaA/viewform?usp=dialog"
442                       target="_blank"
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445                      <span class="icon">
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447                      </span>
448                      <span>Dataset</span>
449                    </a>
450                  </span>
451
452                  <!-- <span class="link-block">
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457                      <span>Code (coming soon)</span>
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460                </div>
461              </div>
462            </div>
463          </div>
464        </div>
465      </div>
466    </section>
467
468    <!-- Teaser image / banner -->
469    <section class="hero teaser">
470      <div class="container is-max-desktop">
471        <div class="hero-body has-text-centered">
472          <img src="Materials/Images/headimage.png" alt="EmoVid overview"
473            style="max-width:100%; border-radius:8px; box-shadow:0 10px 25px rgba(0,0,0,0.08);" loading="eager" />
474          <h2 class="subtitle has-text-centered" style="margin-top:1rem;">
475            EmoVid provides a multimodal, emotion-centric video benchmark for both understanding and generation tasks.
476          </h2>
477        </div>
478      </div>
479    </section>
480    <!-- End teaser image -->
481
482    <!-- Paper abstract -->
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487            <h2 class="title is-3">Abstract</h2>
488            <div class="content has-text-justified">
489              <p>
490                We introduce <strong>EmoVid</strong>, the first multimodal, emotion-annotated video dataset specifically
491                designed for artistic media, which includes cartoon animations, movie clips, and animated stickers. Each
492                video is annotated with emotion labels, visual attributes (brightness, colorfulness, hue), and text
493                captions. Through systematic analysis, we uncover spatial and temporal patterns linking visual features
494                to emotional perceptions across diverse video forms. Building on these insights, we develop an
495                emotion-conditioned video generation technique by fine-tuning the Wan2.1 model. The results show a
496                significant improvement in both quantitative metrics and the visual quality of generated videos for
497                text-to-video and image-to-video tasks.
498              </p>
499            </div>
500          </div>
501        </div>
502      </div>
503    </section>
504    <!-- End paper abstract -->
505
506    <!-- Generation and dataset visualizations -->
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509        <div class="eviz-wrapper">
510          <div class="eviz-header">
511            <h2 class="title is-3">Generation and Dataset Visualizations</h2>
512            <p class="subtitle is-5">Curated multimodal samples from EmoVid, combining representative dataset snippets
513              and controllable custom-role generations.</p>
514          </div>
515
516          <div class="eviz-section">
517            <h3 class="eviz-section-title">📊 Dataset Sample</h3>
518            <p class="eviz-section-subtitle">Tri-modal snippets (animation, movie, sticker) for every emotion class.
519            </p>
520            <div class="eviz-dataset-grid" id="eviz-dataset-content"></div>
521          </div>
522
523          <div class="eviz-section">
524            <h3 class="eviz-section-title">🎭 Custom Roles</h3>
525            <p class="eviz-section-subtitle">Role-conditioned generations showcasing controllable styles.</p>
526            <div class="eviz-custom-grid" id="eviz-custom-content"></div>
527          </div>
528
529        </div>
530      </div>
531    </section>
532    <!-- End Generation and dataset visualizations -->
533
534    <!-- Key Findings -->
535    <section class="section">
536      <div class="container is-max-desktop">
537        <h2 class="title is-3 has-text-centered">Key Findings From EmoVid</h2>
538        <div class="columns is-multiline is-centered is-variable is-4">
539
540          <div class="column is-half">
541            <div class="content">
542              <figure class="image">
543                <img src="Materials/Images/color attributes.png" alt="Color and brightness attributes per emotion"
544                  style="border-radius:8px; box-shadow: 0 8px 16px rgba(0,0,0,0.1);">
545              </figure>
546              <h4 class="title is-6 has-text-centered" style="margin-top: 1rem; margin-bottom: 0.5rem;">Color and
547                Brightness are Strong Emotional Indicators</h4>
548              <p class="has-text-justified">
549                Our analysis of the EmoVid dataset reveals a clear and quantifiable link between low-level visual
550                attributes and high-level emotional categories. We found that positive-valence emotions (like
551                <strong>contentment</strong> and <strong>amusement</strong>) are generally brighter and more colorful.
552                Conversely, high-arousal emotions (like <strong>anger</strong> and <strong>excitement</strong>) also
553                trend towards higher colorfulness but with lower brightness. This spatial layout in the color space
554                supports the robustness of the valence-arousal model.
555              </p>
556            </div>
557          </div>
558
559          <div class="column is-half">
560            <div class="content">
561              <figure class="image">
562                <img src="Materials/Images/user_study.png" alt="User study results"
563                  style="border-radius:8px; box-shadow: 0 8px 16px rgba(0,0,0,0.1);">
564              </figure>
565              <h4 class="title is-6 has-text-centered" style="margin-top: 1rem; margin-bottom: 0.5rem;">Fine-Tuning
566                on EmoVid Decisively Wins User Preference</h4>
567              <p class="has-text-justified">
568                To validate the practical value of our dataset, we fine-tuned the Wan2.1 generative model on EmoVid. In
569                a controlled perceptual user study, our fine-tuned model was overwhelmingly preferred over strong
570                baselines (Wan-Original and CogVideoX). For <strong>Emotion Expression</strong>, our model was ranked
571                first in 66.2% of comparisons. For <strong>Aesthetic Quality</strong>, it achieved a 57.9% Top-1
572                preference rate. This demonstrates EmoVid's clear utility in enhancing the emotional expressiveness of
573                generative models.
574              </p>
575            </div>
576          </div>
577
578          <div class="column is-half">
579            <div class="content">
580              <figure class="image">
581                <img src="Materials/Images/emo_transition_prob.png" alt="Emotion transition matrix"
582                  style="border-radius:8px; box-shadow: 0 8px 16px rgba(0,0,0,0.1);">
583              </figure>
584              <h4 class="title is-6 has-text-centered" style="margin-top: 1rem; margin-bottom: 0.5rem;">Emotions Show
585                Strong Temporal Persistence</h4>
586              <p class="has-text-justified">
587                A key advantage of a video dataset is the ability to study temporal dynamics. By analyzing consecutive
588                movie clips, we built an emotion transition matrix. The analysis shows that emotions have strong
589                self-persistence (the strong diagonal). Furthermore, transitions are far more likely to occur
590                <em>within</em> the same valence (e.g., from one negative emotion to another) than <em>across</em>
591                valences (e.g., from positive to negative).
592              </p>
593            </div>
594          </div>
595
596          <div class="column is-half">
597            <div class="content">
598              <figure class="image">
599                <img src="Materials/Images/keywords.png" alt="Top-5 phrases per emotion"
600                  style="border-radius:8px; box-shadow: 0 8px 16px rgba(0,0,0,0.1);">
601              </figure>
602              <h4 class="title is-6 has-text-centered" style="margin-top: 1rem; margin-bottom: 0.5rem;">Text Captions
603                and Emotion Labels are Strongly Aligned</h4>
604              <p class="has-text-justified">
605                EmoVid is a multimodal dataset, and our analysis confirms its cross-modal consistency. We performed
606                sentiment polarity analysis on the text captions for each video. The results show a clear pattern:
607                videos labeled with positive emotions (e.g., <strong>amusement</strong>, <strong>excitement</strong>,
608                <strong>contentment</strong>) have a significantly higher proportion of positive-sentiment captions, and
609                the same holds true for negative emotions. This confirms the strong semantic link between the textual
610                content and the perceived emotion.
611              </p>
612            </div>
613          </div>
614
615        </div>
616      </div>
617    </section>
618    <!-- End Key Findings -->
619
620    <!--BibTex citation -->
621    <section class="section" id="BibTeX">
622      <div class="container is-max-desktop content">
623        <div class="bibtex-header">
624          <h2 class="title">BibTeX</h2>
625          <button class="copy-bibtex-btn" onclick="copyBibTeX()" title="Copy BibTeX to clipboard">
626            <i class="fas fa-copy"></i>
627            <span class="copy-text">Copy</span>
628          </button>
629        </div>
630        <pre id="bibtex-code"><code>@misc{qiu2025emovidmultimodalemotionvideo,
631  title={EmoVid: A Multimodal Emotion Video Dataset for Emotion-Centric Video Understanding and Generation},
632  author={Zongyang Qiu and Bingyuan Wang and Xingbei Chen and Yingqing He and Zeyu Wang},
633  year={2025},
634  eprint={2511.11002},
635  archivePrefix={arXiv},
636  primaryClass={cs.CV},
637  url={https://arxiv.org/abs/2511.11002},
638}</code></pre>
639      </div>
640    </section>
641    <!--End BibTex citation -->
642  </main>
643
644  
644<script>
645    (function () {
646      const emotions = ['contentment', 'awe', 'amusement', 'excitement', 'sadness', 'disgust', 'fear', 'anger'];
647      const categories = ['animation', 'movie', 'sticker'];
648      const customRoles = [
649        {
650          name: 'chiikawa',
651          displayName: 'Chiikawa I2V',
652          folder: 'chiikawa_i2v',
653          hasInputImage: true,
654          imageFile: 'input_image.png',
655          videoPrefix: 'chiikawa_',
656          subtitle: 'Image-to-Video'
657        },
658        {
659          name: 'labubu',
660          displayName: 'Labubu I2V',
661          folder: 'labubu_i2v',
662          hasInputImage: true,
663          imageFile: 'input_image.jpg',
664          videoPrefix: 'labubu_',
665          subtitle: 'Image-to-Video'
666        },
667        {
668          name: 'ishowspeed',
669          displayName: 'iShowSpeed I2V',
670          folder: 'ishowspeed_i2v',
671          hasInputImage: true,
672          imageFile: 'input_image.jpg',
673          videoPrefix: 'speed_',
674          subtitle: 'Image-to-Video'
675        },
676        {
677          name: 'ghibli',
678          displayName: 'Ghibli T2V',
679          folder: 'ghibli_t2v',
680          hasInputImage: false,
681          ghibliText: 'Studio Ghibli style prompt',
682          videoPrefix: 'ghibli_',
683          subtitle: 'Text-to-Video'
684        }
685      ];
686
687      const sampleVideos = {
688        contentment: {
689          animation: ['Aladdin_scene_1131_instance_0_1.mp4', 'How to Keep a Mummy_scene_308_instance_1_1.mp4'],
690          movie: ['-mexzYsMSro_clip_010.mp4', '0nfoP3bmd1c_clip_024.mp4'],
691          sticker: ['13047851479713149078.mp4', '4165678996664452379.mp4']
692        },
693        awe: {
694          animation: ['How to Keep a Mummy_scene_369_instance_0_1.mp4', 'ID:INVADED_scene_251_instance_1_1.mp4'],
695          movie: ['-c9-2KcnLXI_clip_004.mp4', '0mRRULBvuj0_clip_010.mp4'],
696          sticker: ['1151841417982281027.mp4', '693624055024178899.mp4']
697        },
698        amusement: {
699          animation: ['Snow White and the Seven Dwarfs_scene_482_instance_0_1.mp4', 'jiujijinghua_07_scene_298_instance_0_1.mp4'],
700          movie: ['DUMW--Zlrcs_clip_033.mp4', 'gnbjy2tWfd4_clip_012.mp4'],
701          sticker: ['1014953795366610078.mp4', '7313602290956595969.mp4']
702        },
703        excitement: {
704          animation: ['The Little Mermaid_scene_253_instance_0_1.mp4', 'The Tigger Movie_scene_646_instance_0_2.mp4'],
705          movie: ['3Sz7dbX2kTY_clip_017.mp4', '_KC5AJdRgBs_clip_045.mp4'],
706          sticker: ['155648567990388098.mp4', '1779437211223867166.mp4']
707        },
708        sadness: {
709          animation: ['How to Keep a Mummy_scene_208_instance_0_1.mp4', 'My Youth Romantic Comedy Is Wrong, as I Expected_scene_307_instance_0_1.mp4'],
710          movie: ['0tRSAQUheo0_clip_021.mp4', '3sP7UMxhGYw_clip_096.mp4'],
711          sticker: ['123466421705187905.mp4', '12414244761973568755.mp4']
712        },
713        disgust: {
714          animation: ['Snow White and the Seven Dwarfs_scene_68_instance_0_1.mp4', 'Tower of God_scene_141_instance_0_1.mp4'],
715          movie: ['3JLDAyAEaqI_clip_031.mp4', '7kihC0VFaQE_clip_038.mp4'],
716          sticker: ['10355761199465314392.mp4', '1538353539352474088.mp4']
717        },
718        fear: {
719          animation: ['Atlantis: The Lost Empire_scene_1353_instance_1_1.mp4', 'How to Keep a Mummy_scene_207_instance_1_1.mp4'],
720          movie: ['0-81bpcuz44_clip_042.mp4', '0p9Q6tDJJ1w_clip_008.mp4'],
721          sticker: ['2518671278090971395.mp4', '909784035520128291.mp4']
722        },
723        anger: {
724          animation: ['Aladdin_scene_1351_instance_0_1.mp4', "Xam'd: Lost Memories_scene_235_instance_0_1.mp4"],
725          movie: ['-oPHsR72Lfo_clip_045.mp4', '_nSQhWq7etg_clip_020.mp4'],
726          sticker: ['4367649449949661050.mp4', '7666337384347304302.mp4']
727        }
728      };
729
730      const customContainer = document.getElementById('eviz-custom-content');
731      const datasetContainer = document.getElementById('eviz-dataset-content');
732
733      function src(path) {
734        return encodeURI(path);
735      }
736
737      function renderCustom() {
738        if (!customContainer) return;
739        let html = '';
740        customRoles.forEach(role => {
741          const imageHtml = role.hasInputImage
742            ? `<img src="${src('Materials/generation results/custom roles/' + role.folder + '/' + role.imageFile)}" alt="${role.displayName} reference" class="eviz-input-image" loading="lazy">`
743            : `<div class="eviz-role-note">${role.ghibliText}</div>`;
744
745          html += `
746            <div class="eviz-role">
747              <h3>${role.displayName}<span>${role.subtitle}</span></h3>
748              ${imageHtml}
749              <div class="eviz-emotions-grid">
750          `;
751
752          emotions.forEach(emotion => {
753            const videoSrc = src(`Materials/generation results/custom roles/${role.folder}/${role.videoPrefix}${emotion}.mp4`);
754            html += `
755              <div class="eviz-emotion-video">
756                <h4>${emotion}</h4>
757                <video autoplay muted loop playsinline preload="auto" loading="lazy">
758                  <source src="${videoSrc}" type="video/mp4">
759                </video>
760              </div>
761            `;
762          });
763
764          html += `
765              </div>
766            </div>
767          `;
768        });
769
770        customContainer.innerHTML = html;
771      }
772
773      function renderDataset() {
774        if (!datasetContainer) return;
775        let html = '';
776        emotions.forEach(emotion => {
777          const entries = sampleVideos[emotion];
778          if (!entries) return;
779          html += `
780            <div class="eviz-dataset-emotion">
781              <h3>${emotion}</h3>
782              <div class="eviz-dataset-categories">
783          `;
784
785          categories.forEach(category => {
786            const files = entries[category] || [];
787            html += `
788              <div class="eviz-dataset-category">
789                <h5>${category}</h5>
790                <div class="category-videos">
791            `;
792
793            files.forEach(file => {
794              const videoSrc = src(`Materials/dataset sample/${emotion}/${category}/video/${file}`);
795              html += `
796                <video autoplay muted loop playsinline preload="auto" loading="lazy">
797                  <source src="${videoSrc}" type="video/mp4">
798                </video>
799              `;
800            });
801
802            html += `
803                </div>
804              </div>
805            `;
806          });
807
808          html += `
809              </div>
810            </div>
811          `;
812        });
813        datasetContainer.innerHTML = html;
814      }
815
816      renderCustom();
817      renderDataset();
818    })();
819  </script>
819
820
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